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{"poster":"CamilleRule34","date":"2018-06-10T02:44:53.664+0000","title":"I just re-rolled 3 shitty skins into Aether Wing Kayle","subforum":"General Discussion","up_votes":1,"down_votes":0,"body":"I don't play her at all but its a nice skin, and I'm really happy about it. Thought i'd tell yall.","replies":[]}
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{"poster":"Kayos Pendragon","date":"2015-04-23T10:53:37.000+0000","title":"Champion Concept-Harute the Feared Beserker","subforum":"Player Creations","embed":{"description":null,"url":"http://imgur.com/a/pcLz4","image":"http://i.imgur.com/HEzg2nf.jpg"},"up_votes":1,"down_votes":1,"body":"okay its my second champion design it comes with the default skin left image on the link, and the other skin is like soul-reaver or something, right image on the link (*the img on the right does look like nightmare from soul calibre, that wasn&#039;t my intentions but anyway hope you enjoy and tell me what you think)-will be making his brother soon!! XD\r\n\r\n**Champion**: Harute, The Feared Bezerker \r\n**Lanes/Role**: Tank, Fighter \r\n**Lore**: Harute wasn&#039;t as feared and dangerous as he is today. Before, when he was a child in Ionia, he was happy, kind, and a gentle boy. Until one fateful day. Caught in the middle of the war between Noxius and Demacia, his village was the battlefield ending many lives of his people. Him and his big brother were caught by Noxian forces. After years of torturing for information they decided for them to be executed.\r\nBoth feeling scared of dying, the executioner gave them a chance knowing that they will not make it to the exit. In a desperate attempt to escape, Harute stalled the executioner long enough for his big brother to escape, when it was his turn to vanish he wasn&rsquo;t so lucky: losing an arm and severe blood loss.\r\nBoth barely making it out alive they enter the slums on Noxus territory. With the amount of blood loss from his severed arm, it was most likely he wouldn&#039;t make it. As he breathed his last breath, his brother called out for help, but no one listened. However, a Witch of the Black Rose made him a deal, saving his life for the cost of his brother&#039;s freedom. He accepted knowing that this will save his life. The witch gave Harute a set of armor. After putting it on, Harute fainted. Waking up and shocked to see his arm again, Harute had started to feel complete. What he didn&rsquo;t know was that the armor was defected and it slowly drove him insane. Challenging anyone who got in his way, he joined the rift to see if there was anyone that could put an end to his madness.\r\n&#039;He&#039;s an enemy feared by all who face him, those who survive are severely traumatized &lsquo;~Frightened Noxian General\r\n\r\n**Base Stats**:\r\nHealth- 650 (+75 per level)\r\nFury- 100 \r\nHealth Regen- 8 (+0.25 per level)\r\nFury Regen- 2.5 per second\r\nAttack Damage- 69 (+5 per level)\r\nAbility Power- 2 (+0.5 per level)\r\nAttack Speed- 0.8\r\nCrit Chance- 5%\r\nMovement Speed- 355\r\nArmor- 35 (75 when lvl 18)\r\nMagic Resist- 20 (+2.4 per level)\r\n\r\n**What Makes this Champion Unique?**\r\nWell, I talked to my friends about this and they thought it was good however they included another so now I got two options and both are really good so I&#039;ll get right to it... please choose one that you think is better (look below)\r\n**Option 1:**\r\nThat all of his moves contains a passive when maxed out (except R, which is gained already when reaching lvl 6)\r\nGeneral Passive: Honed Blade- Every 4th AA will deal additional damage based on 5% of enemy&rsquo;s maximum health \r\nQ- Each AA will cause a stack known as &#039;Chaotic fury&#039; which gives him an additional 2 attack damage (max stacks 5)\r\nW- When the fury bar is full he gains increased movement speed\r\nE- He gains an increase of armor and magic resist based on how much enemy champions he hits with this move (+5 per champ) for a limited time\r\nR- If he successfully Qs an enemy Champion he will absorb their passive (*note this will only work if possible, such as Vayne&#039;s W, or Pantheon&#039;s E, or Jax&#039;s R, Etc.) for a limited time (probably only for 10s).\r\n\r\n**Option 2:**\r\nPassive: Soul Eater-When he kills minions, monsters, or champions he gains souls in which he gains stacks soon benefitting him after reaching a certain amount.\r\n(Minions/Monsters=1, Large minions/Large monsters/ Enemy Champions=2)\r\n100- Consumes less fury when using W as well as increase regen of it\r\n200- Q will now have a longer range with an additional 0.5 duration to the enemy \r\n300- R will now have a slight increase on its range\r\n400- An increase of base stats by 10% (too much? IDK...)\r\n\r\n**Skills:**\r\nPassive: well simple you got option 1 or or option 2, whichever is best and unique\r\nQ: Dark Impalement, Cost=no cost, Cool Down=10s (maxed out=6s), Range=975\r\nHe throws his blade toward any target based on where your cursor is, dealing physical damage 50 (+5% of your total attack damage) (+5% per level). Also knocking them back and pressing Q will make you rush towards your blade and deal 5% damage on next AA, also if this hits the enemy near a wall or something that will cause collision will cause them to be stunned.\r\nW: Dark Armor Shroud, Cost=5 fury per second, Cool Down=3s\r\nToggle on- releases dark particles from the armor which deals 30 Ability power to nearby enemies (+5% of ap) \r\nToggle off- Regens 2.5 fury per second (AA will increase regen from 2.5 to 5 per second)\r\nE: Devastating Cleave, Cost= no cost, Cool Down=15s, Range=650\r\nHe charges a heavy 180 degrees side swing left or right depending on location of cursor (left side=right swing, right side=left swing) dealing 100 damage (+0 physical damage) however if the enemy hits a wall it deals an extra 100 damage as well as applying a 30% slow and 5% damage reduction.\r\nR: Chaos Breaker, Cost=50 fury, Cool down=105s, Range=400\r\nHe splits his giant broad sword in half to make 2 blades giving a slightly longer AA range, empowers Q so that he can do it twice, and gains an increase of attack speed +50% (maxing this out will be put almost up to the maximum attack speed limit). However decreases the maximum damage output by 10% (the faster you AA the decrease damage output is increased).\r\n\r\n**Sayings when being selected in Champ select:**\r\n&#039;This world will be covered with bodies soaked in a river of blood.&#039;\r\n**Sayings when heading to Destination:**\r\n&#039;Give me a worthy opponent&#039;\r\n&#039;Is there a challenger there?&#039;\r\n&#039;You can run, but you can&#039;t hide brother&#039;\r\n&#039;My sword is getting thirsty&#039; \r\n**Sayings when heading to Attack:**\r\n&#039;All that will be left is blood dripping down my blade&#039;\r\n(Loud manic-like screaming)\r\n&#039;All must perish&#039;\r\n&#039;Only the strong survive&#039;\r\n**Joke1:**\r\n&#039;I had my arm cut off, and no I&rsquo;m not all-right...&#039;\r\n**Joke2/taunt:**\r\n&#039;Let me kill you, so you can be a part of me&#039;\r\n&#039;I&#039;m not satisfied, bring in more warriors&#039;\r\n**Dance:**\r\nSplits his sword in half and starts juggling \r\n**Laugh:**\r\nManiac type laughter which may echo\r\n**Hidden Taunts:**\r\n&#039;Ahh... finally a challenger approaches&#039;\r\nOnly when there is an enemy Fiora, Pantheon, Aatrox, Xererath, Jax or Draven.\r\n**Recall:**\r\nWhen recalling his armor slowly opens and shows some souls getting out of the armor/ out of him","replies":[{"poster":"Ned FIanders","date":"2015-04-24T20:46:15.230+0000","up_votes":2,"down_votes":0,"body":"\"the img on the right does look like nightmare from soul calibre, that wasn't my intentions\"\nBull fucking shit mate. You might be able to fool someone with no knowledge of Soul Calibre but you cant fool someone who grew up with it.\n\nhttp://img1.wikia.nocookie.net/__cb20130131131925/villains/images/c/c9/Nightmare_IV.jpg\n\nIll give you props on what appears to be a decent vector of Nightmare but don't fucking try to plagiarize my favorite game >:|\n\nGod you even traced the wisps of soul energy from his back >.<","replies":[{"poster":"Kayos Pendragon","date":"2015-04-25T11:01:20.510+0000","up_votes":1,"down_votes":0,"body":"dude calm down I love soul calibre as much as the next guy but it would be a cool skin design... ill just rework on the skin if that what will make u happy?","replies":[{"poster":"Ned FIanders","date":"2015-04-25T21:35:15.887+0000","up_votes":1,"down_votes":0,"body":"You really cant rework an idea if its already being used. Do what the original creators of Nightmare did and think long and hard about what you want to create. Then, with enough effort and time, you can make something without having to resort to plagiarism.","replies":[{"poster":"Kayos Pendragon","date":"2015-04-26T00:39:46.802+0000","up_votes":1,"down_votes":0,"body":"I would but I already know for a fact that the chances of my champ concpets to be actually in the league are really low...\n\nHowever, i am committed to my posts as well as the comments made by other people because of that I will work on this but I got so many other things to do since I got my friends champ design skin designs suggested by summoners and I got school so all im asking you is to have patience and wait and the redesign should be here","replies":[]}]}]}]},{"poster":"Technoman21","date":"2015-04-24T08:40:54.922+0000","up_votes":1,"down_votes":0,"body":"His joke should be \"No im not 'armless\" {{champion:35}} {{champion:35}} {{champion:35}} {{champion:35}} {{champion:35}}","replies":[{"poster":"Kayos Pendragon","date":"2015-04-24T13:54:47.638+0000","up_votes":1,"down_votes":0,"body":"haha why not have both?","replies":[]}]}]}
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{ "name": "devcondapp", "displayName": "devcondapp" }
{"latitude":37.0169,"longitude":-121.578,"zipcode":"95020","msa":"7400","dma":"807","state":"CA"}
c({"name": "filters", "type": "attribute", "comment": "<p>Filters.</p>", "attribute_type": "@type Object", "src": "appDev/node_modules/nodeunit/deps/ejs/lib/ejs.js", "line": 19, "children": []})
{"HISTORY":"<!-- --><br>ColdFusion 9: Added this tag.<br>","SYNTAX":"<!-- --><br>&lt;cfprogressbar \r\n autoDisplay=&quot;true|false&quot; \r\n name=&quot;<i xmlns:fn=\"http:\/\/www.w3.org\/2005\/xpath-functions\" xmlns:fo=\"http:\/\/www.w3.org\/1999\/XSL\/Format\" xmlns:xs=\"http:\/\/www.w3.org\/2001\/XMLSchema\">control identifier<\/i>&quot; \r\n bind =&quot;<i xmlns:fn=\"http:\/\/www.w3.org\/2005\/xpath-functions\" xmlns:fo=\"http:\/\/www.w3.org\/1999\/XSL\/Format\" xmlns:xs=\"http:\/\/www.w3.org\/2001\/XMLSchema\">bind expression<\/i>&quot; \r\n duration=&quot;<i xmlns:fn=\"http:\/\/www.w3.org\/2005\/xpath-functions\" xmlns:fo=\"http:\/\/www.w3.org\/1999\/XSL\/Format\" xmlns:xs=\"http:\/\/www.w3.org\/2001\/XMLSchema\">time value<\/i>&quot; \r\n height=&quot;<i xmlns:fn=\"http:\/\/www.w3.org\/2005\/xpath-functions\" xmlns:fo=\"http:\/\/www.w3.org\/1999\/XSL\/Format\" xmlns:xs=\"http:\/\/www.w3.org\/2001\/XMLSchema\">height in pixels<\/i>&quot; \r\n interval=&quot;<i xmlns:fn=\"http:\/\/www.w3.org\/2005\/xpath-functions\" xmlns:fo=\"http:\/\/www.w3.org\/1999\/XSL\/Format\" xmlns:xs=\"http:\/\/www.w3.org\/2001\/XMLSchema\">time in milliseconds<\/i>&quot; \r\n onComplete=&quot;<i xmlns:fn=\"http:\/\/www.w3.org\/2005\/xpath-functions\" xmlns:fo=\"http:\/\/www.w3.org\/1999\/XSL\/Format\" xmlns:xs=\"http:\/\/www.w3.org\/2001\/XMLSchema\">function name<\/i>&quot; \r\n onError=&quot;<i xmlns:fn=\"http:\/\/www.w3.org\/2005\/xpath-functions\" xmlns:fo=\"http:\/\/www.w3.org\/1999\/XSL\/Format\" xmlns:xs=\"http:\/\/www.w3.org\/2001\/XMLSchema\">JavaScript function name<\/i>&quot; \r\n style=&quot;<i xmlns:fn=\"http:\/\/www.w3.org\/2005\/xpath-functions\" xmlns:fo=\"http:\/\/www.w3.org\/1999\/XSL\/Format\" xmlns:xs=\"http:\/\/www.w3.org\/2001\/XMLSchema\">style specification<\/i>&quot; \r\n width=&quot;<i xmlns:fn=\"http:\/\/www.w3.org\/2005\/xpath-functions\" xmlns:fo=\"http:\/\/www.w3.org\/1999\/XSL\/Format\" xmlns:xs=\"http:\/\/www.w3.org\/2001\/XMLSchema\">pixel value<\/i>&quot; &gt;<br>","CATEGORY":"Display management tags","PAGENAME":"cfprogressbar","SEEALSO":"","DESCRIPTION":"Defines a progress bar to indicate the progress of an activity such as a file download.","LICENCE":"http:\/\/help.adobe.com\/en_US\/ColdFusion\/10.0\/LegalNotices\/index.html","EXAMPLE":"<!-- --><br>The following uses a simple comment form, and uses a timer to simulate the time it would take to process the form.<br>The Application.cfc page must enable session management.<br>The main application page contains the following code:<br>&lt;!DOCTYPE html PUBLIC &quot;-\/\/W3C\/\/DTD XHTML 1.0 Transitional\/\/EN&quot; &quot;http:\/\/www.w3.org\/TR\/xhtml1\/DTD\/xhtml1-transitional.dtd&quot;&gt; \r\n&lt;html xmlns=&quot;http:\/\/www.w3.org\/1999\/xhtml&quot;&gt; \r\n&lt;head&gt; \r\n&lt;meta http-equiv=&quot;Content-Type&quot; content=&quot;text\/html; charset=iso-8859-1&quot; \/&gt; \r\n&lt;title&gt;Untitled Document&lt;\/title&gt; \r\n&lt;\/head&gt; \r\n \r\n&lt;script type=&quot;text\/javascript&quot;&gt; \r\n\/\/ The function that starts the progress bar, \r\n\/\/ called when the user clicks the Send comment button. \r\nfunction startProgress() { \r\n ColdFusion.ProgressBar.start(&quot;mydataProgressbar&quot;); \r\n }; \r\n \r\n\/\/ The function called when the progress bar finishes, \r\n\/\/ specified by the cfprogressbar tag onComplete attribute. \r\nfunction onfinish() { \r\n alert(&quot;Done&quot;); \r\n }; \r\n&lt;\/script&gt; \r\n \r\n&lt;body&gt; \r\n&lt;!--- Ensure there is no Session.STATUS value, which is used by \r\n the progress bar bind CFC, when the page displays. ---&gt; \r\n&lt;cfif IsDefined(&quot;Session.STATUS&quot;)&gt; \r\n &lt;cfscript&gt; \r\n StructDelete(Session,&quot;STATUS&quot;); \r\n &lt;\/cfscript&gt; \r\n&lt;\/cfif&gt; \r\n \r\n&lt;!--- For code simplicity, formatting is minimal. ---&gt; \r\n&lt;cfform name=&quot;kitform&quot;&gt; \r\n &lt;p&gt;To make our service better and to benefit from our special offers, \r\n take a moment to give us your email address and send us a comment.&lt;\/p&gt; \r\n &lt;p&gt;Name:&lt;br \/&gt; \r\n &amp;nbsp;&lt;cfinput type=&quot;text&quot; name=&quot;name&quot;&gt; &lt;\/p&gt; \r\n &lt;p&gt;E-mail:&lt;br \/&gt; \r\n &amp;nbsp;&lt;cfinput type=&quot;text&quot; name=&quot;email&quot;&gt; &lt;\/p&gt; \r\n &lt;p&gt;Comment:&lt;br \/&gt; \r\n &amp;nbsp;&lt;cftextarea name=&quot;cmnt&quot;\/&gt;&lt;\/p&gt; \r\n &lt;p&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; \r\n &lt;cfinput type=&quot;button&quot; name=&quot;&quot; value=&quot;Send Comment&quot; \r\n onClick=startProgress()&gt;&lt;\/p&gt; \r\n &lt;!--- The progressbar control ---&gt; \r\n &lt;div style=&quot;padding-left:3px&quot; &gt; \r\n &lt;cfprogressbar name=&quot;mydataProgressbar&quot; \r\n bind=&quot;cfc:mycfc.getstatus()&quot; \r\n interval=&quot;1700&quot; \r\n width=&quot;200&quot; \r\n oncomplete=&quot;onfinish&quot;\/&gt; \r\n &lt;\/div&gt; \r\n \r\n&lt;\/cfform&gt; \r\n&lt;\/body&gt; \r\n&lt;\/html&gt;<br>The mycfc.cfc file has a single <samp class=\"codeph\">getstatus<\/samp> function:<br>&lt;cfcomponent&gt; \r\n&lt;!--- This function simulates the time taken \r\n by and operation by using sleep functions. \r\n It increments the progressbar status by 1\/10 each time the \r\n progressbar bind expression calls it (that is, each time the \r\n time specified by the cfprogressbar interval attribute passes. \r\n---&gt; \r\n &lt;cffunction name=&quot;getstatus&quot; access=&quot;remote&quot;&gt; \r\n &lt;cfset str = StructNew()&gt; \r\n &lt;cfset str.message = &quot;Saving Data&quot;&gt; \r\n &lt;cfif NOT IsDefined(&quot;session.STATUS&quot;)&gt; \r\n &lt;cfset session.STATUS = 0.1&gt; \r\n &lt;cfscript&gt; \r\n Sleep(200); \r\n &lt;\/cfscript&gt; \r\n &lt;cfelseif session.STATUS LT 0.9&gt; \r\n &lt;cfset session.STATUS=session.STATUS + .1&gt; \r\n &lt;cfscript&gt; \r\n Sleep(200); \r\n &lt;\/cfscript&gt; \r\n &lt;cfelse&gt; \r\n &lt;cfset str.message = &quot;Done...&quot;&gt; \r\n &lt;cfset session.STATUS=&quot;1.0&quot;&gt; \r\n &lt;\/cfif&gt; \r\n &lt;cfset str.status = session.STATUS&gt; \r\n &lt;cfreturn str&gt; \r\n &lt;\/cffunction&gt; \r\n \r\n&lt;\/cfcomponent&gt;<br>","USAGE":"<!-- --><br>A progress bar has one of two behaviors:<br><li><p>Manual, where the progress indicator length increases steadily over a time specified by the <samp class=\"codeph\">duration<\/samp> attribute.<\/p> <\/li> \n<li><p>Dynamic, where the <samp class=\"codeph\">bind<\/samp> attribute specifies a function that determines the indicator length.<\/p> <\/li><br>If you use a bind expression, the called function takes no parameters, and must return a structure with two values:<br><li><p><samp class=\"codeph\">status<\/samp> - A decimal completion value, in the range 0 -1.0<\/p> <\/li> \n<li><p><samp class=\"codeph\">message<\/samp> - A message to display in the progress bar, such as “Loading...” or “Completed”.<\/p> <\/li><br>You use two Ajax functions to start and stop the progress bar:<br>ColdFusion.ProgressBar.start(<i xmlns:fn=\"http:\/\/www.w3.org\/2005\/xpath-functions\" xmlns:fo=\"http:\/\/www.w3.org\/1999\/XSL\/Format\" xmlns:xs=\"http:\/\/www.w3.org\/2001\/XMLSchema\">barName<\/i>) \r\nColdFusion.ProgressBar.stop(<i xmlns:fn=\"http:\/\/www.w3.org\/2005\/xpath-functions\" xmlns:fo=\"http:\/\/www.w3.org\/1999\/XSL\/Format\" xmlns:xs=\"http:\/\/www.w3.org\/2001\/XMLSchema\">barName<\/i>)<br>You must call the <samp class=\"codeph\">start<\/samp> method to start the progress bar.<br>You call the <samp class=\"codeph\">stop<\/samp> method to explicitly stop the progress bar. The bar stops automatically when the bind method returns a <samp class=\"codeph\">status<\/samp> value of 1 or the period specified by the <samp class=\"codeph\">duration<\/samp> attribute elapses. Therefore, you need to use this method only if a process does not complete, if the process completes before the <samp class=\"codeph\">duration<\/samp> period, or in other nonstandard situations, such as error conditions.<br>","Attribute":[{"REQOROPT":"Optional","DESCRIPTION":"Set to true to display the progress bar.","default":true,"Attribute":"autoDisplay"},{"REQOROPT":"Required","DESCRIPTION":"The control name. Used to refer to the control in JavaScript, for example in the script that starts the progress.","default":"","Attribute":"name"},{"REQOROPT":"Required if duration is not specified","DESCRIPTION":"A bind expression specifying a client JavaScript function or server CFC that the control calls to get progress information each time the period defined by the interval attribute elapses. You cannot use this attribute with a duration attribute. If an error occurs, no further bind expression calls are triggered and onError is called (if defined).","default":"","Attribute":"bind"},{"REQOROPT":"Required if bind is not specified","DESCRIPTION":"The time, in milliseconds, between when the bar starts showing progress and when it shows completed progress. Use only on automatic progress bars that do not use a bind expression to get actual progress information. You cannot use this attribute with a bind attribute.","default":"","Attribute":"duration"},{"REQOROPT":"Optional","DESCRIPTION":"Height of the bar in pixels.","default":" ","Attribute":"height"},{"REQOROPT":"Optional","DESCRIPTION":"Used if duration is specified. The time interval, in milliseconds, at which the progress bar updates. Although this attribute is optional, specify it to prevent the bar from updating frequently.","default":1000,"Attribute":"interval"},{"REQOROPT":"Optional","DESCRIPTION":"The name of a function to call when progress completes.","default":"","Attribute":"onComplete"},{"REQOROPT":" ","DESCRIPTION":"Applies only if you use bind. The JavaScript function to run on an error condition. The error can be a network error or server-side error.","default":" ","Attribute":"onError"},{"REQOROPT":"Optional","DESCRIPTION":"The following are the supported colors: bgcolor: The background color for the progress bar. A hexadecimal value without “#” prefixed. textcolor: Text color on progress bar. progresscolor: Color used to indicate the progress.","default":" ","Attribute":"style"},{"REQOROPT":"Optional","DESCRIPTION":"The width (length) of the bar in pixels.","default":400,"Attribute":"width"}]}
{"category": "Criminal Appeal", "status": "Remittitur Issued/Case Closed", "case_url": "http://caseinfo.nvsupremecourt.us/public/caseView.do?csIID=5092", "caption": "KELLY (JEREMY) VS. STATE", "type": "Life", "case_no": "39204", "subtype": "Post-Conviction/Proper Person", "parties": [{"Represented By": "In Proper Person", "Role": "Appellant", "Party Name": "Jeremy Bryan Kelly"}, {"Represented By": "Attorney General/Carson City", "Role": "Respondent", "Party Name": "The State of Nevada"}], "docket": [{"Date": "02/19/2002", "Type/Subtype": "Filing Fee - Filing Fee Waived", "Description": "Filing Fee Waived."}, {"Type/Subtype": "Notice of Appeal Documents - Notice of Appeal/Proper Person", "Description": "Filed Certified Copy of Notice of Appeal/Proper Person. Appeal docketed in the Supreme Court this day.", "Document Number": "02-03117", "Document URL": "/document/view.do?csNameID=5092&csIID=5092&deLinkID=65004&sireDocumentNumber=02-03117", "Date": "02/19/2002", "Pending?": "NA"}, {"Type/Subtype": "Order/Procedural - Order to Transmit Judgment or Order and Record on Appeal", "Description": "Filed Order re: Transmit Judgment or Order and Record on Appeal. Certified copy of final order due: 30 days. Certified copy of the Record on Appeal due: 120 days. fn2[The record shall not include any exhibits filed in the district court].", "Document Number": "02-04336", "Document URL": "/document/view.do?csNameID=5092&csIID=5092&deLinkID=66039&sireDocumentNumber=02-04336", "Date": "03/11/2002", "Pending?": "NA"}, {"Type/Subtype": "Notice of Appeal Documents - District Court Order/Judgment", "Description": "Filed District Court Order/Judgment. Certified copy of Findings of Fact, Conclusions of Law and Order filed in district court on: February 26, 2002.", "Document Number": "02-05103", "Document URL": "/document/view.do?csNameID=5092&csIID=5092&deLinkID=66634&sireDocumentNumber=02-05103", "Date": "03/21/2002", "Pending?": "NA"}, {"Date": "04/29/2002", "Type/Subtype": "Motion - Proper Person Motion", "Description": "Received Proper Person Motion. Motion for Leave to Proceed on Appeal in Proper Persons."}, {"Date": "04/29/2002", "Type/Subtype": "Brief - Proper Person Brief", "Description": "Received Proper Person Brief. Appellant's Proper Persons Opening Brief."}, {"Type/Subtype": "Record on Appeal Documents - Record on Appeal Copy", "Description": "Filed Record on Appeal Copy. Volumes 1 through 19.", "Document Number": "02-12261", "Document URL": "/document/view.do?csNameID=5092&csIID=5092&deLinkID=72067&sireDocumentNumber=02-12261", "Date": "07/17/2002", "Pending?": "NA"}, {"Date": "07/17/2002", "Type/Subtype": "Case Status Update - Submitted for Decision", "Description": "Submitted for Decision."}, {"Date": "08/12/2002", "Type/Subtype": "Notice/Incoming - Proper Person Notice", "Description": "Received Proper Person Notice. Notice to the Court Clerk Change of Address."}, {"Type/Subtype": "Order/Dispositional - Dispositional Order/Appeal", "Description": "Filed Dispositional Order/Appeal. Order of Affirmance and Limited Remand to Correct Judgment of Conviction. We conclude that oral argument and briefing are unwarranted in this matter. \"ORDER the judgment of the district court AFFIRMED and REMAND this matter to the district court for the limited purpose of entering a corrected judgment of conviction.\" fn46[We have considered all proper person documents filed or received in this matter. We conclude that appellant is entitled only to the relief described herein.] NNP03-RR/WM/MG", "Document Number": "03-04514", "Document URL": "/document/view.do?csNameID=5092&csIID=5092&deLinkID=83359&sireDocumentNumber=03-04514", "Date": "03/18/2003", "Pending?": "NA"}, {"Type/Subtype": "Remittitur - Remittitur", "Description": "Issued Remittitur.", "Document Number": "03-04630", "Document URL": "/document/view.do?csNameID=5092&csIID=5092&deLinkID=84849&sireDocumentNumber=03-04630", "Date": "04/15/2003", "Pending?": "NA"}, {"Date": "04/15/2003", "Type/Subtype": "Case Status Update - Remittitur Issued/Case Closed", "Description": "Remittitur Issued/Case Closed."}, {"Type/Subtype": "Remittitur - Remittitur", "Description": "Filed Remittitur. Received by County Clerk on April 17, 2003.", "Document Number": "03-04630", "Document URL": "/document/view.do?csNameID=5092&csIID=5092&deLinkID=85369&sireDocumentNumber=03-04630", "Date": "04/28/2003", "Pending?": "NA"}], "filed.date": "02/19/2002", "metadata": {"To SP/Judge:": "NA", "Lower Court Case(s):": "Clark Co. - Eighth Judicial District - C137479", "Related Case(s):": ",", "Submission Date:": "07/17/2002", "Panel Assigned:": "Panel", "Case Status:": "Remittitur Issued/Case Closed", "Replacement:": "NA", "Oral Argument Location:": "NA", "Classification:": "Criminal Appeal - Life - Post-Conviction/Proper Person", "Oral Argument:": "NA", "Disqualifications:": "NA", "SP Status:": "NA", "Short Caption:": "KELLY (JEREMY) VS. STATE", "How Submitted:": "On Record"}}
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{ "forum_title": "Vefsíðugerð", "user": "kindin", "user_id": "26714", "date": "2007-09-25 12:20:07", "title": "HugaPHP?", "text": "Sælir vefarar, ég var að spá hvort það sé hægt að mixa sér eins konar “myndir í bið” teljara fyrir hugakerfið? Einhver búinn að pæla í þessu, eða er þetta löngu útpælt?", "url": "https://www.hugi.is/vefsidugerd/korkar/545009/hugaphp/", "url_id": "545009", "id": "5261138", "replies": [ { "user": "frantic89", "user_id": "6497", "date": "2007-09-26 13:35:48", "id": "5263697", "reply_to_id": "5261138", "text": "Held að þú verðir bara að spyrja vefstjóra af þessu.\nÞú þarft líklegast að tengjast gagnagrunni." } ] }
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{"poster":"Laughing Fish","date":"2015-07-19T21:54:49.054+0000","title":"When you think you are winning, but then the enemy Nasus teleports in with 1000 stacks","subforum":"Memes & Games","up_votes":71,"down_votes":8,"body":"https://usatftw.files.wordpress.com/2015/02/0tzifkb.gif?w=641&amp;h=358","replies":[{"poster":"JesterSummoner","date":"2015-07-19T22:52:27.222+0000","up_votes":20,"down_votes":0,"body":"As a Seahawk fan.... the pain is double lol","replies":[{"poster":"arc95","date":"2015-07-20T01:16:56.925+0000","up_votes":9,"down_votes":0,"body":"i would rather have a 1000 stack {{champion:75}} Tp right on top of me than relive that day...WHY NOT RUN THE BALL... WHY Q_Q","replies":[{"poster":"DeathToHeretics","date":"2015-07-20T03:54:20.455+0000","up_votes":5,"down_votes":0,"body":"Because M.L. had a terrible record when it came to rushing into the T.D. zone, but then again I don't know much sportsball.","replies":[]}]},{"poster":"Laughing Fish","date":"2015-07-20T13:24:10.425+0000","up_votes":5,"down_votes":0,"body":"As a Patriots fan, my reaction to that moment was closer to:\nhttps://michaelpiff.files.wordpress.com/2015/02/brady-super-bowl-gif.gif","replies":[{"poster":"LOL Spammer","date":"2015-07-20T14:57:45.062+0000","up_votes":4,"down_votes":0,"body":"Patriots fans unite!\nhttp://i.imgur.com/3I0NJ5I.gif\n","replies":[]},{"poster":"JesterSummoner","date":"2015-07-20T15:30:42.370+0000","up_votes":2,"down_votes":0,"body":"I was a Patriots fan when I was younger when I watched Super Bowl XXXVI. I remember cowering behind a stool watching the final kick by Vinatieri. I became more of a Seahawk fan as I got older because my whole family are die hard fans. I still highly respect the Patriots.","replies":[]},{"poster":"Celeste Benal","date":"2015-07-20T15:05:40.317+0000","up_votes":2,"down_votes":0,"body":"> [{quoted}](name=Laughing Fish,realm=NA,application-id=Ir7ZrJjF,discussion-id=mEvpHN7t,comment-id=00020002,timestamp=2015-07-20T13:24:10.425+0000)\n>\n> As a Patriots fan, my reaction to that moment was closer to:\n> https://michaelpiff.files.wordpress.com/2015/02/brady-super-bowl-gif.gif\n\nThis. So much this.","replies":[{"poster":"Laughing Fish","date":"2015-07-20T15:16:06.225+0000","up_votes":2,"down_votes":0,"body":"When you find a fellow Patriots fan:\nhttps://usatthebiglead.files.wordpress.com/2015/01/tom-brady-is-pumped-about-blowout-of-indianapolis-afc-championship.gif?w=1000","replies":[]}]},{"poster":"The Lexer","date":"2015-07-21T02:29:15.105+0000","up_votes":1,"down_votes":0,"body":"I hate the Patriots....","replies":[]}]},{"poster":"PickleBabah","date":"2015-07-20T07:41:59.371+0000","up_votes":2,"down_votes":0,"body":"It hurts so much... Like a kick to the nuts","replies":[]}]},{"poster":"Ironclad Dragon","date":"2015-07-20T06:58:42.848+0000","up_votes":12,"down_votes":0,"body":"When you're trying to recall but see Nasus heading toward you:\nhttp://media.giphy.com/media/ZFtynI5ftVxkY/giphy.gif","replies":[]},{"poster":"I Main Swain","date":"2015-07-20T16:41:46.741+0000","up_votes":6,"down_votes":0,"body":"https://sjoycarlson.files.wordpress.com/2014/10/home-alone.gif","replies":[]},{"poster":"Kuroi86","date":"2015-07-20T03:46:58.593+0000","up_votes":6,"down_votes":0,"body":"{{champion:54}} top\n{{champion:80}} jung\n{{champion:90}} mid\n{{champion:67}} adc\n{{champion:1}} supp\n\nI'm sorry, was there a Nasus? I didn't notice, he seems to have vanished shortly after the rest of his team did.","replies":[]},{"poster":"Academy Kayn","date":"2015-07-20T03:06:30.693+0000","up_votes":6,"down_votes":0,"body":"http://2.bp.blogspot.com/-Y_ODcECzxGQ/T4sMKffGa8I/AAAAAAAAA88/LnQ8Dvynqbg/s1600/michael-scott-no.gif","replies":[{"poster":"LOL Spammer","date":"2015-07-20T14:59:17.914+0000","up_votes":3,"down_votes":0,"body":"http://media.giphy.com/media/W9WSk4tEU1aJW/giphy.gif","replies":[{"poster":"Academy Kayn","date":"2015-07-20T17:17:00.538+0000","up_votes":3,"down_votes":0,"body":"http://img1.wikia.nocookie.net/__cb20101230190127/uncyclopedia/images/0/0c/Shaking_head.gif","replies":[{"poster":"LOL Spammer","date":"2015-07-20T20:18:15.348+0000","up_votes":2,"down_votes":0,"body":"http://mrwgifs.com/wp-content/uploads/2013/03/Chuck-Norris-Approves-With-A-Thumbs-Up.gif","replies":[{"poster":"Academy Kayn","date":"2015-07-20T20:24:39.733+0000","up_votes":3,"down_votes":0,"body":"http://utahpoliticohub.com/wp-content/uploads/2015/04/thumbs-down.gif","replies":[]}]}]}]}]},{"poster":"WutsKraken","date":"2015-07-20T02:33:03.890+0000","up_votes":2,"down_votes":0,"body":"But then {{champion:48}} lands a godly pillar and ults him therefore preventing Nasus from doing anything","replies":[{"poster":"Vistha Kai","date":"2015-07-20T07:48:58.535+0000","up_votes":7,"down_votes":1,"body":"You missed the part in which nobody plays Trundle.","replies":[{"poster":"Confron7a7ion7","date":"2015-07-20T19:42:51.510+0000","up_votes":2,"down_votes":0,"body":"{{champion:48}} is MASSIVELY under appreciated.","replies":[]},{"poster":"Magik Digitz","date":"2015-07-20T10:26:41.916+0000","up_votes":2,"down_votes":0,"body":"I do","replies":[{"poster":"Hello I am Bird","date":"2015-07-20T16:03:28.208+0000","up_votes":3,"down_votes":1,"body":"Get out.","replies":[]}]}]}]},{"poster":"Schenix","date":"2015-07-20T15:21:32.570+0000","up_votes":2,"down_votes":1,"body":"I feel you used this situation just to mock Seahawk fans...\n\n\n\nAnd I approve.","replies":[{"poster":"Laughing Fish","date":"2015-07-20T15:32:52.679+0000","up_votes":5,"down_votes":0,"body":"I would *never* do something like that.\nhttp://media.tumblr.com/tumblr_m9hqs6fMK71rpt0rh.gif","replies":[]}]},{"poster":"The Fire on Fire","date":"2015-07-20T14:42:55.986+0000","up_votes":1,"down_votes":0,"body":"yes but everything is good when you are teemo {{champion:17}} {{champion:17}} {{champion:17}} {{champion:17}} {{champion:17}} {{champion:17}} {{champion:17}}","replies":[{"poster":"Laughing Fish","date":"2015-07-20T15:03:15.601+0000","up_votes":5,"down_votes":0,"body":"Or when you are gankplank. 9 foot tall god of death begins rapidly aging you, causing your body to wither away? Eat an orange, be k.","replies":[{"poster":"CrazedPorcupine","date":"2015-07-20T18:43:48.561+0000","up_votes":1,"down_votes":0,"body":"Or Garen and his Q.","replies":[{"poster":"BeatzBoyFTW","date":"2015-07-21T02:34:02.751+0000","up_votes":1,"down_votes":0,"body":"Or Darius with the god amount of bleeding zoning control.","replies":[]}]}]}]},{"poster":"360D3GR3SS","date":"2015-07-20T06:57:09.754+0000","up_votes":2,"down_votes":0,"body":"http://static.tumblr.com/ab9b2b06f9c56811940ec35475bca78a/whnwjik/1rOmj5ql5/tumblr_static___sticker_375x360.png","replies":[{"poster":"Laughing Fish","date":"2015-07-20T15:04:06.935+0000","up_votes":4,"down_votes":0,"body":"http://38.media.tumblr.com/a7a7145e9cdc9ccd204c5438620cc70a/tumblr_n40gifPWRi1rrnep7o1_500.gif","replies":[]}]},{"poster":"Mr Borg","date":"2015-07-20T04:58:47.094+0000","up_votes":3,"down_votes":0,"body":"Seahawks fan here. I hate you for reminding me of this moment.","replies":[{"poster":"Laughing Fish","date":"2015-07-20T12:49:03.136+0000","up_votes":2,"down_votes":0,"body":"Patriots fan here:\nhttps://michaelpiff.files.wordpress.com/2015/02/russell-int.gif","replies":[{"poster":"ArkenStorm","date":"2015-07-20T16:49:43.897+0000","up_votes":2,"down_votes":0,"body":"i don't even like professional sports and that is just painful to watch. so sad","replies":[{"poster":"Laughing Fish","date":"2015-07-20T16:51:04.969+0000","up_votes":1,"down_votes":0,"body":"It was a glorious moment.","replies":[{"poster":"ArkenStorm","date":"2015-07-20T17:42:40.579+0000","up_votes":1,"down_votes":0,"body":"like I watch college football(BYU, yay for Utah) and I understand the significance. it was stupid of them not to run it that close, and the closeness of the catch is just painful for the seahawks lol","replies":[{"poster":"Laughing Fish","date":"2015-07-20T17:47:11.136+0000","up_votes":1,"down_votes":0,"body":"Not necessarily. Beast Mode has a poor record at making those short redzone runs. The Seahawks made plays like that all year long, and 99% of the time it worked for them. The only reason people consider it foolish was because it was intercepted. It is just funny that the time it failed was when that much was on the line. The mentality they played with won them one Superbowl and brought them to another.","replies":[{"poster":"ArkenStorm","date":"2015-07-20T18:04:18.531+0000","up_votes":1,"down_votes":0,"body":"I think it's foolish because IMO anytime you are that close, you should run it and hope your brute force will get it in. Was that 4th down? if it was, i can understand the pass a bit more, but If it was 1st-3rd down I would have run it for sure","replies":[{"poster":"Laughing Fish","date":"2015-07-20T18:06:48.985+0000","up_votes":1,"down_votes":0,"body":"The thing is the Seahawks only made it to the Superbowl and got in that position by doing things like passing in a seemingly obvious run play. That was simply how the team played, and they made it to back-to-back superbowls that way, winning one of them.","replies":[{"poster":"ArkenStorm","date":"2015-07-20T18:10:31.320+0000","up_votes":1,"down_votes":0,"body":"Oh, well see, I had no idea about that. But still, if that was what they did, You would think the opposing team would pick up on that, like the Patriots did(I guess?), and they should have gone against what they usually do to throw the opposing team off. W/e, like I said, I don't really like, nor do I follow any professional sports of any kind, and tbh I only follow college sports of BYU because my dad likes to, and Spend time with dad wooo","replies":[{"poster":"Laughing Fish","date":"2015-07-20T18:17:16.591+0000","up_votes":1,"down_votes":0,"body":"Well that is exactly what happened. The Seahawks often threw on redzone plays with great success, and the Patriots tended to be quite poor at actually stopping redzone passes. Malcom Butler (Patriots player that made the interception) had been very bad at stopping similar plays (failing in practice to stop that exact play several times), but before the Superbowl he drastically changed how he handled redzone passes, ignoring the opposing player and focusing completely on the football. Evidently it worked.\n\n If the pass had worked, people would have been talking about how Bulter just ignored the other players and let them score. Both teams made it to the Superbowl by being aggressive and taking risks. The Patriot's risks just paid off slightly more than the Seahawk's risks.","replies":[{"poster":"ArkenStorm","date":"2015-07-20T18:26:14.866+0000","up_votes":1,"down_votes":0,"body":"thank you for enlightening me. And now i will use this information to taunt people >:D\nlol no really though, youre probably right, I can still have my opinion that you should always run the ball with 5> yards to go","replies":[{"poster":"Laughing Fish","date":"2015-07-20T18:35:58.663+0000","up_votes":1,"down_votes":0,"body":"The thing is if you *always* run with less than 5 yards, the other team *will* find a way to stop you. You can never be that predicable. A team as elite as the Patriots can only be beaten by not letting them know what you are planning.","replies":[{"poster":"ArkenStorm","date":"2015-07-20T18:37:33.591+0000","up_votes":1,"down_votes":0,"body":"fair point. and this is why i don't play/coach sports XD.\nAlthough I do think that having your biggest guy just charge through works pretty darn well. at least in college","replies":[{"poster":"ArkenStorm","date":"2015-07-20T18:43:15.951+0000","up_votes":2,"down_votes":0,"body":"(holy reply thread batman!)\nand this is why I play video games, because I have no idea XD\n\n(evidently I cannot actually reply to you)","replies":[]},{"poster":"Laughing Fish","date":"2015-07-20T18:39:33.677+0000","up_votes":1,"down_votes":0,"body":"Lol, yeah in college that method can work. But in the NFL even the bad players are still very strong and impressively fast.","replies":[]}]}]}]}]}]}]}]},{"poster":"Mr Borg","date":"2015-07-21T15:11:09.312+0000","up_votes":1,"down_votes":0,"body":"I don't mind them passing there, and Caroll's reasoning was sound. But I don't like the route. You're almost guaranteed to get a touchdown with Lynch since he can move a pile a few yards by himself, and you have two chances. So why throw a crossing route that is probably the highest completion percentage, but also the most likely to get picked. I would have much preferred a fade route or a bootleg with one receiver in the back of the end zone and a tight end near the goal line (although time may have been a factor for that)","replies":[]}]}]}]}]}]}]},{"poster":"NommyPancake","date":"2015-07-20T01:35:14.783+0000","up_votes":2,"down_votes":0,"body":"https://youtu.be/L4GeEhBOC_E\n\nTeh what the pancake moment :^)","replies":[]},{"poster":"Toa of Death","date":"2015-07-19T22:39:15.434+0000","up_votes":2,"down_votes":0,"body":"lol this gif is perfect for so many jokes. This is probably the third or fourth time I've seen it on here.","replies":[]}]}
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{"poster":"troler108","date":"2018-01-16T01:18:39.718+0000","title":"se busca main supp oro + para team","subforum":"Reclutamiento","up_votes":3,"down_votes":1,"body":"nos falta uno y somos buena onda ph\n\n\nPD: el ruhos , tenochtitlan y sir baneado son los candidatos seleccionados , digan dia para organizarnos y jugar un dia con cada uno po","replies":[{"poster":"Narut0 Gut","date":"2018-01-16T19:25:05.813+0000","up_votes":1,"down_votes":0,"body":"aca ex oro main sup\nagreguen pa jugar las posicionamiento","replies":[]},{"poster":"SirBaneado","date":"2018-01-16T02:35:42.034+0000","up_votes":1,"down_votes":0,"body":"A mi me gustaria! Soy oro y tengo una champion pool bastante amplia! espero tu respuesta{{champion:497}}","replies":[]},{"poster":"Ruhos","date":"2018-01-16T01:29:42.019+0000","up_votes":1,"down_votes":0,"body":"agrega","replies":[]},{"poster":"l iDuKeE l","date":"2018-01-16T01:20:57.394+0000","up_votes":1,"down_votes":0,"body":"CHICOS HOY NO HAY MAINCRAF{{summoner:11}}","replies":[]}]}
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{"poster":"Dawnation","date":"2016-04-07T21:12:47.717+0000","title":"Frage aufgrund einiger Keyboard-Funktionen","subforum":"Hilfe & Support","up_votes":1,"down_votes":0,"body":"Hey Leute, ich benutze zur Zeit eine Logitech G510S und h&auml;tte dazu einige fragen, da ich mir nicht sicher bin, ob diese Features erlaubt sind.\r\n\r\nZuerst einmal besitzt das Keyboard ein kleines Display, &uuml;ber das man kleinere Apps von Logitech benutzen kann, darunter such eines f&uuml;r LoL welches automatisch installiert wird sobald LoL auf dem PC erkannt ist.\r\n\r\nDieses zeigt einem eine kleine Statistik (KDA zusammengefasst, plazierte/zerst&ouml;rte Wards\r\nCS etc.) Ist die nutzung diesrs Features erlaubt ?\r\n\r\n\r\nZu guter letzt geht es mir um die G-Tasten aka. Makrotasten, das besch&auml;ftigt mich am meisten, diese kann man leider nicht direkt im Spiel zu irgendeiner Aktion binden, sondern manuell &uuml;ber die Software.\r\nIch wei&szlig;, dass es nicht erlaubt ist bspw. ein Wardjumpmakro zu benutzen (Darum geht es aber auch nicht).\r\n\r\nDie Tastatur ist recht gro&szlig; und ich habe eher kleine H&auml;nde weshalb ich mich schwer tue CTRL+1-6 damit zu bet&auml;tigen, da ich die Emotes doch ab und zu gern mal benutze .. w&auml;re es erlaubt diese Tastenkombis auf diese Tasten zu legen ? (W&auml;re um einiges leichter, da diese direkt links von QWER liegen)\r\n\r\nW&uuml;rde mich dort mal &uuml;ber ein Statement freuen bevor ich da evtl. etwas doch nicht ganz erlaubtes tue, Unwissenheit sch&uuml;tzt ja bekanntlich nicht vor Strafen. :)","replies":[{"poster":"Poroclysm","date":"2016-04-07T21:21:48.246+0000","up_votes":2,"down_votes":0,"body":"Da du die Einstellungen auch direkt ingame vornehmen kannst, sollte das eigentlich kein Problem sein.\nIch hab meine Makrotasten auch schon seit Ewigkeiten darauf eingestellt, meine Abilities zu leveln, da meine Hand recht klein ist und es anstrengend ist, immer Strg+Q/W/E/R zu drücken.","replies":[]},{"poster":"Sakunosuke Oda","date":"2016-04-08T10:57:28.627+0000","up_votes":1,"down_votes":0,"body":"Darum habe ich mal ein Thread gemacht und mir wurde gesagt das es erlaubt ist allerdings ganze Kombos Flash Ult E Q W Combos etc sind verboten moment gebe dir ein Link rein\nhttp://boards.euw.leagueoflegends.com/de/c/hilfe-support-de/dr1rEiRu-mehrtasten-maause-und-tastaturen-verboten \ndie letzte antwort","replies":[]},{"poster":"DerSucher","date":"2016-04-07T22:25:07.412+0000","up_votes":1,"down_votes":0,"body":"Servus Dawnation,\n\nzuerst einmal ganz klare Antwort! Makros sind verboten, jeglicher Art. Dazu komme ich aber gleich.\n\nDas mit deinem Display kommt darauf an, ob diese App als Drittprogramm agiert oder nur online die Daten abruft wie z.B. LoLNexus.com. \nEin Drittprogramm ist verboten und auch Bannbar. Da Riot in letzer zeit da verschärft drüber geht wollte ich das nur gesagt haben.\n\nZum Thema Markos. Diese sind auch verboten und dürfen nicht benutzt werden. Theoretisch. Wenn du diese aber z.B. für STRG+6 Benutzt darfst du sie benutzen, da sie dir keinen Spielvorteil gibt. \nSollte die Marko aber ganze kombos oder skills schnell level ist dies verboten und ebenfalls bannbar. \n\nDazu muss man aber sagen, dass die benutzung von Makrotasten nicht bewiesen werden kann. Solltest du aber desöfteren deswegen reportet werden wird durchgezogen egal was du dem support sagst. \n\n\nMeine Empfehlung an dich. Benutzt am besten keine App und am besten auch keine Makros. Gewöhn dich daran mit STRG und der Taste deine sachen zu leveln und Co. Das brauchst du ebenfalls in anderen Spielen. \nAlternativen zur App gibt es genügend.\n\n\nGruß DerSucher\n\nP.S. Suchst du eine Community? Komm vorbei. TS: ct.ts.io","replies":[{"poster":"Crounty","date":"2016-04-08T04:12:29.081+0000","up_votes":1,"down_votes":0,"body":"Ich hätte gerne eine Quelle dazu, denn mir sagte der Support, dass die Nutzung von Makros erlaubt sind, wenn man sie wie normale Tasten benutzt. Kombos sind tatsächlich verboten.","replies":[]},{"poster":"Dawnation","date":"2016-04-08T04:03:15.523+0000","up_votes":1,"down_votes":0,"body":"Hey, danke für die Antwort. :)\nZur Sache mit den Skills.. das mache ich seit Jahren so, aber bei den Zahlen ist der Abstand dann halt doch ein wenig größer als bei QWER ^^.\n\nDas Display hab ich eig. nach dem ersten Spiel damit abgeschaltet, da es ja quasi nur das zusammenfasst, was man sowieso sieht, vorrangig ging es ja wirklich darum die Makrotasten mit CTRL+1-6 zu belegen damit ich da nicht immer 'nen Krampf in der Hand bekomme. \nCombos habe ich ja oben mit dem Wardjump als Beispiel schon erwähnt, dass ich das nicht vorhabe. :)","replies":[]}]},{"poster":"Nycaria","date":"2016-04-07T23:42:28.487+0000","up_votes":1,"down_votes":0,"body":"Schreib am besten einfach den Support an um auf Nummer sicher zu gehen :)","replies":[]}]}
{ "forum_title": "Hugbúnaðar- & Forritunarstofan", "id": "32579", "title": "edit: Vantar Keylogger/\"púkann\" í Ubuntu", "url": "https://spjall.vaktin.is/viewtopic.php?f=7&t=32579", "posts": [ { "user_name": "zdndz", "text": "Getur einhver hjálpað mér, vantar keylogger og er með linux ubuntu..?\nedit: annað en þarna lkl dótið\neinhver? \nEDIT nr. 2!: Ef einhver veit um svona keylogger má endilega láta mig vita en annað sem mér vantar sem ég heyrði af veit einhver hvað forritið heitir sem er eins og púkinn nema er fyrir linux ubuntu og hægt að láta leiðrétta fyrir íslenskan texta, það væri vel þegið ef einhver gæti komið með nafnið á þessu drasli", "date": "2010-09-15 22:45:00", "post_id": "282271", "reply_to_id": false }, { "user_name": "zdndz", "text": "upserí upserí", "date": "2010-09-18 19:31:00", "post_id": "282714", "reply_to_id": "282271" }, { "user_name": "gardar", "text": "http://github.com/stebbiv/OpenOffice-Spelling-is/\nhttps://launchpad.net/hunspell-is", "date": "2010-09-18 21:17:00", "post_id": "282721", "reply_to_id": "282714" }, { "user_name": "zdndz", "text": "danke sun", "date": "2010-09-18 21:39:00", "post_id": "282724", "reply_to_id": "282721" } ], "date": "2010-09-15 22:45:00" }
{ "name": "vue-cmap", "version": "0.0.4", "author": "doodlewind", "description": "vue China map component", "main": "CMap.vue", "scripts": { "test": "echo \"Error: no test specified\" && exit 1" }, "keywords": [ "map", "china", "vue" ], "dependencies": { "autoprefixer": "^6.5.0", "babel-core": "^6.0.0", "babel-loader": "^6.2.8", "babel-plugin-transform-runtime": "^6.15.0", "babel-polyfill": "^6.16.0", "babel-preset-es2015": "^6.0.0", "css-loader": "^0.25.0", "file-loader": "^0.9.0", "json-loader": "^0.5.4", "leaflet": "^1.0.1", "style-loader": "^0.13.1", "url-loader": "^0.5.7", "vue": "^2.0.1", "vue-loader": "^9.9.5", "vue-style-loader": "^1.0.0" } }
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{"notes": [{"id": "BJl65sA9tm", "original": "Bkg70-DqKX", "number": 575, "cdate": 1538087829081, "ddate": null, "tcdate": 1538087829081, "tmdate": 1545355377286, "tddate": null, "forum": "BJl65sA9tm", "replyto": null, "invitation": "ICLR.cc/2019/Conference/-/Blind_Submission", "content": {"title": "Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations", "abstract": "Imitation learning aims to learn an optimal policy from expert demonstrations and its recent combination with deep learning has shown impressive performance. However, collecting a large number of expert demonstrations for deep learning is time-consuming and requires much expert effort. In this paper, we propose a method to improve generative adversarial imitation learning by using additional information from non-expert demonstrations which are easier to obtain. The key idea of our method is to perform multiclass classification to learn discriminator functions where non-expert demonstrations are regarded as being drawn from an extra class. Experiments in continuous control tasks demonstrate that our method learns better policies than the generative adversarial imitation learning baseline when the number of expert demonstrations is small.", "keywords": ["Imitation learning", "Generative adversarial imitation learning"], "authorids": ["voot.tangkaratt@riken.jp", "sugi@k.u-tokyo.ac.jp"], "authors": ["Voot Tangkaratt", "Masashi Sugiyama"], "TL;DR": "We improve GAIL by learning discriminators using multiclass classification with non-expert regarded as an extra class.", "pdf": "/pdf/3bd7072ceff083939e4740be0cd7f1f2ef0dffdc.pdf", "paperhash": "tangkaratt|improving_generative_adversarial_imitation_learning_with_nonexpert_demonstrations", "_bibtex": "@misc{\ntangkaratt2019improving,\ntitle={Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations},\nauthor={Voot Tangkaratt and Masashi Sugiyama},\nyear={2019},\nurl={https://openreview.net/forum?id=BJl65sA9tm},\n}"}, "signatures": ["ICLR.cc/2019/Conference"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2019/Conference"], "details": {"replyCount": 14, "writable": false, "overwriting": [], "revisions": true, "tags": [], "invitation": {"id": "ICLR.cc/2019/Conference/-/Blind_Submission", "rdate": null, "ddate": null, "expdate": null, "duedate": 1538085600000, "tmdate": 1538142958393, "tddate": null, "super": null, "final": null, "reply": {"signatures": {"values": ["ICLR.cc/2019/Conference"]}, "forum": null, "readers": {"values": ["everyone"]}, "replyto": null, "content": {"authorids": {"values-regex": ".*"}, "authors": {"values": ["Anonymous"]}}, "writers": {"values": ["ICLR.cc/2019/Conference"]}}, "signatures": ["ICLR.cc/2019/Conference"], "readers": ["everyone"], "nonreaders": [], "invitees": ["~"], "noninvitees": [], "writers": ["ICLR.cc/2019/Conference"], "multiReply": null, "taskCompletionCount": null, "transform": null, "cdate": 1538142958393}}, "tauthor": "OpenReview.net"}, {"id": "BJlNkgC-g4", "original": null, "number": 1, "cdate": 1544835036000, "ddate": null, "tcdate": 1544835036000, "tmdate": 1545354531639, "tddate": null, "forum": "BJl65sA9tm", "replyto": "BJl65sA9tm", "invitation": "ICLR.cc/2019/Conference/-/Paper575/Meta_Review", "content": {"metareview": "This paper proposes a variant of GAIL that can learn from both expert and non-expert demonstrations. The paper is generally well-written, and the general topic is of interest to the ICLR community. Further, the empirical comparisons provide some interesting insights. However, the reviewers are concerned that the conceptual contribution is quite small, and that the relatively small conceptual contribution also does not lead to large empirical gains. As such, the paper does not meet the bar for publication at ICLR.", "confidence": "4: The area chair is confident but not absolutely certain", "recommendation": "Reject", "title": "meta-review"}, "signatures": ["ICLR.cc/2019/Conference/Paper575/Area_Chair1"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2019/Conference/Paper575/Area_Chair1"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations", "abstract": "Imitation learning aims to learn an optimal policy from expert demonstrations and its recent combination with deep learning has shown impressive performance. However, collecting a large number of expert demonstrations for deep learning is time-consuming and requires much expert effort. In this paper, we propose a method to improve generative adversarial imitation learning by using additional information from non-expert demonstrations which are easier to obtain. The key idea of our method is to perform multiclass classification to learn discriminator functions where non-expert demonstrations are regarded as being drawn from an extra class. Experiments in continuous control tasks demonstrate that our method learns better policies than the generative adversarial imitation learning baseline when the number of expert demonstrations is small.", "keywords": ["Imitation learning", "Generative adversarial imitation learning"], "authorids": ["voot.tangkaratt@riken.jp", "sugi@k.u-tokyo.ac.jp"], "authors": ["Voot Tangkaratt", "Masashi Sugiyama"], "TL;DR": "We improve GAIL by learning discriminators using multiclass classification with non-expert regarded as an extra class.", "pdf": "/pdf/3bd7072ceff083939e4740be0cd7f1f2ef0dffdc.pdf", "paperhash": "tangkaratt|improving_generative_adversarial_imitation_learning_with_nonexpert_demonstrations", "_bibtex": "@misc{\ntangkaratt2019improving,\ntitle={Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations},\nauthor={Voot Tangkaratt and Masashi Sugiyama},\nyear={2019},\nurl={https://openreview.net/forum?id=BJl65sA9tm},\n}"}, "tags": [], "invitation": {"id": "ICLR.cc/2019/Conference/-/Paper575/Meta_Review", "rdate": null, "ddate": null, "expdate": null, "duedate": 1541548800000, "tmdate": 1545353165342, "tddate": null, "super": null, "final": null, "reply": {"forum": "BJl65sA9tm", "replyto": "BJl65sA9tm", "readers": {"description": "Select all user groups that should be able to read this comment. Selecting 'All Users' will allow paper authors, reviewers, area chairs, and program chairs to view this comment.", "values": ["everyone"]}, "signatures": {"description": "How your identity will be displayed with the above content.", "values-regex": "ICLR.cc/2019/Conference/Paper575/Area_Chair[0-9]+"}, "writers": {"description": "Users that may modify this record.", "values-regex": "ICLR.cc/2019/Conference/Paper575/Area_Chair[0-9]+"}, "content": {"title": {"order": 1, "value-regex": ".{1,500}", "description": "Brief summary of your review.", "required": true}, "metareview": {"order": 2, "value-regex": "[\\S\\s]{1,5000}", "description": "Please provide an evaluation of the quality, clarity, originality and significance of this work, including a list of its pros and cons.", "required": true}, "recommendation": {"order": 3, "value-dropdown": ["Accept (Oral)", "Accept (Poster)", "Reject"], "required": true}, "confidence": {"order": 4, "value-radio": ["5: The area chair is absolutely certain", "4: The area chair is confident but not absolutely certain", "3: The area chair is somewhat confident", "2: The area chair is not sure", "1: The area chair's evaluation is an educated guess"], "required": true}}}, "signatures": ["ICLR.cc/2019/Conference"], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2019/Conference/Paper575/Area_Chairs"], "noninvitees": [], "writers": ["ICLR.cc/2019/Conference"], "multiReply": false, "taskCompletionCount": null, "transform": null, "cdate": 1545353165342}}}, {"id": "HygVmDfS14", "original": null, "number": 11, "cdate": 1544001307716, "ddate": null, "tcdate": 1544001307716, "tmdate": 1544001307716, "tddate": null, "forum": "BJl65sA9tm", "replyto": "BygodKhSAQ", "invitation": "ICLR.cc/2019/Conference/-/Paper575/Official_Comment", "content": {"title": "I still think that my raised issues are valid. ", "comment": "Addressing 1)\nThe submission assumes a huge amount of non-expert data (2-3 orders of magnitude more than expert data). I think that it is not realistic to assume that such amounts of data are collected while familiarizing with kinesthetic teaching. Furthermore, in practice, we often need to adjust data collection while familiarizing with the task, and collecting/post-processing data can be laborious as well. Hence, I still don't think that the approach is relevant for robotics.\n\nAddressing 2)\nI am mainly missing an experiment that shows a useful application of the approach. It is not very surprising that using a huge amount of non-expert data is better than not using it. However, can you show the benefit of the approach on a problem with a realistic split of expert and non-expert data?\n\nAddressing first 3)\nI don't think that we can argue about expert data collection being safer than autonomous data collection, when using an approach that relies on a large amount of autonomous system interactions.\n\nAddressing both 4s)\nI still think, that the theoretical contribution is very small and the practical benefits are marginal as well. It seems rather obvious that additionally using a large amount of close-to-expert data can improve the efficiency of GAIL and any IL/IRL approach in general. Hence, I do not think that demonstrating this is a significant contribution. The submission neither shows a convincing application for the problem setting, nor a convincing method to make use of the additional data. V-GAIL and U-GAIL are very naive baselines and still, they perform similar and sometimes even outperform M-GAIL. It is not enough to perform better than GAIL when using a massive amount of additional information, if you can not beat naive baselines that use the same amount of information. There are various other ways of using this data somehow that can undoubtedly benefit from it, e.g. initializing the GAIL policy with BC trained on all data, building a regularizer from the non-expert data (and potentially decreasing its influence during optimization), fitting a distribution to the non-expert data to learn the discriminator using importance weighting, and many more. I would expect an ICLR/NIPS/ICML/AAAI paper on this topic to outperform such naive baselines by several orders of magnitude in terms of the required number of non-expert data.\n\nAddressing 5)\nThanks for removing this section.\n"}, "signatures": ["ICLR.cc/2019/Conference/Paper575/AnonReviewer3"], "readers": ["everyone"], "nonreaders": ["ICLR.cc/2019/Conference/Paper575/Reviewers/Unsubmitted"], "writers": ["ICLR.cc/2019/Conference/Paper575/AnonReviewer3", "ICLR.cc/2019/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations", "abstract": "Imitation learning aims to learn an optimal policy from expert demonstrations and its recent combination with deep learning has shown impressive performance. However, collecting a large number of expert demonstrations for deep learning is time-consuming and requires much expert effort. In this paper, we propose a method to improve generative adversarial imitation learning by using additional information from non-expert demonstrations which are easier to obtain. The key idea of our method is to perform multiclass classification to learn discriminator functions where non-expert demonstrations are regarded as being drawn from an extra class. Experiments in continuous control tasks demonstrate that our method learns better policies than the generative adversarial imitation learning baseline when the number of expert demonstrations is small.", "keywords": ["Imitation learning", "Generative adversarial imitation learning"], "authorids": ["voot.tangkaratt@riken.jp", "sugi@k.u-tokyo.ac.jp"], "authors": ["Voot Tangkaratt", "Masashi Sugiyama"], "TL;DR": "We improve GAIL by learning discriminators using multiclass classification with non-expert regarded as an extra class.", "pdf": "/pdf/3bd7072ceff083939e4740be0cd7f1f2ef0dffdc.pdf", "paperhash": "tangkaratt|improving_generative_adversarial_imitation_learning_with_nonexpert_demonstrations", "_bibtex": "@misc{\ntangkaratt2019improving,\ntitle={Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations},\nauthor={Voot Tangkaratt and Masashi Sugiyama},\nyear={2019},\nurl={https://openreview.net/forum?id=BJl65sA9tm},\n}"}, "tags": [], "invitation": {"id": "ICLR.cc/2019/Conference/-/Paper575/Official_Comment", "rdate": null, "ddate": null, "expdate": null, "duedate": null, "tmdate": 1543621614845, "tddate": null, "super": null, "final": null, "reply": {"forum": "BJl65sA9tm", "replyto": null, "readers": {"description": "Select all user groups that should be able to read this comment.", "value-dropdown-hierarchy": ["everyone", "ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference/Paper575/Reviewers", "ICLR.cc/2019/Conference/Paper575/Area_Chairs", "ICLR.cc/2019/Conference/Program_Chairs"]}, "nonreaders": {"values": ["ICLR.cc/2019/Conference/Paper575/Reviewers/Unsubmitted"]}, "signatures": {"description": "", "values-regex": "ICLR.cc/2019/Conference/Paper575/AnonReviewer[0-9]+|ICLR.cc/2019/Conference/Paper575/Authors|ICLR.cc/2019/Conference/Paper575/Area_Chair[0-9]+|ICLR.cc/2019/Conference/Program_Chairs"}, "writers": {"description": "Users that may modify this record.", "values-copied": ["ICLR.cc/2019/Conference", "{signatures}"]}, "content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters).", "required": true}}}, "signatures": ["ICLR.cc/2019/Conference"], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2019/Conference/Paper575/Reviewers", "ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference/Paper575/Area_Chairs", "ICLR.cc/2019/Conference/Program_Chairs"], "noninvitees": [], "writers": ["ICLR.cc/2019/Conference"], "multiReply": true, "taskCompletionCount": null, "transform": null, "cdate": 1543621614845}}}, {"id": "SkxKXT29A7", "original": null, "number": 10, "cdate": 1543322912642, "ddate": null, "tcdate": 1543322912642, "tmdate": 1543322912642, "tddate": null, "forum": "BJl65sA9tm", "replyto": "SkxNXhhYCQ", "invitation": "ICLR.cc/2019/Conference/-/Paper575/Official_Comment", "content": {"title": "About the tables", "comment": "In the revision, all Tables are moved to appendix (page 26-29). We did not evaluate statistical significant because it is unreliable given only 5 samples."}, "signatures": ["ICLR.cc/2019/Conference/Paper575/Authors"], "readers": ["everyone"], "nonreaders": ["ICLR.cc/2019/Conference/Paper575/Reviewers/Unsubmitted"], "writers": ["ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations", "abstract": "Imitation learning aims to learn an optimal policy from expert demonstrations and its recent combination with deep learning has shown impressive performance. However, collecting a large number of expert demonstrations for deep learning is time-consuming and requires much expert effort. In this paper, we propose a method to improve generative adversarial imitation learning by using additional information from non-expert demonstrations which are easier to obtain. The key idea of our method is to perform multiclass classification to learn discriminator functions where non-expert demonstrations are regarded as being drawn from an extra class. Experiments in continuous control tasks demonstrate that our method learns better policies than the generative adversarial imitation learning baseline when the number of expert demonstrations is small.", "keywords": ["Imitation learning", "Generative adversarial imitation learning"], "authorids": ["voot.tangkaratt@riken.jp", "sugi@k.u-tokyo.ac.jp"], "authors": ["Voot Tangkaratt", "Masashi Sugiyama"], "TL;DR": "We improve GAIL by learning discriminators using multiclass classification with non-expert regarded as an extra class.", "pdf": "/pdf/3bd7072ceff083939e4740be0cd7f1f2ef0dffdc.pdf", "paperhash": "tangkaratt|improving_generative_adversarial_imitation_learning_with_nonexpert_demonstrations", "_bibtex": "@misc{\ntangkaratt2019improving,\ntitle={Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations},\nauthor={Voot Tangkaratt and Masashi Sugiyama},\nyear={2019},\nurl={https://openreview.net/forum?id=BJl65sA9tm},\n}"}, "tags": [], "invitation": {"id": "ICLR.cc/2019/Conference/-/Paper575/Official_Comment", "rdate": null, "ddate": null, "expdate": null, "duedate": null, "tmdate": 1543621614845, "tddate": null, "super": null, "final": null, "reply": {"forum": "BJl65sA9tm", "replyto": null, "readers": {"description": "Select all user groups that should be able to read this comment.", "value-dropdown-hierarchy": ["everyone", "ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference/Paper575/Reviewers", "ICLR.cc/2019/Conference/Paper575/Area_Chairs", "ICLR.cc/2019/Conference/Program_Chairs"]}, "nonreaders": {"values": ["ICLR.cc/2019/Conference/Paper575/Reviewers/Unsubmitted"]}, "signatures": {"description": "", "values-regex": "ICLR.cc/2019/Conference/Paper575/AnonReviewer[0-9]+|ICLR.cc/2019/Conference/Paper575/Authors|ICLR.cc/2019/Conference/Paper575/Area_Chair[0-9]+|ICLR.cc/2019/Conference/Program_Chairs"}, "writers": {"description": "Users that may modify this record.", "values-copied": ["ICLR.cc/2019/Conference", "{signatures}"]}, "content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters).", "required": true}}}, "signatures": ["ICLR.cc/2019/Conference"], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2019/Conference/Paper575/Reviewers", "ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference/Paper575/Area_Chairs", "ICLR.cc/2019/Conference/Program_Chairs"], "noninvitees": [], "writers": ["ICLR.cc/2019/Conference"], "multiReply": true, "taskCompletionCount": null, "transform": null, "cdate": 1543621614845}}}, {"id": "HylZUHEvAQ", "original": null, "number": 8, "cdate": 1543091529310, "ddate": null, "tcdate": 1543091529310, "tmdate": 1543091529310, "tddate": null, "forum": "BJl65sA9tm", "replyto": "r1eMyU2rR7", "invitation": "ICLR.cc/2019/Conference/-/Paper575/Official_Comment", "content": {"title": "Reply to rebuttal", "comment": "Thank you for responding to my concerns. The difference between M-GAIL, GAIL, and GAIL with sub-optimal demonstrations (i.e. U-GAIL) seem very minor theoretically, and there does not appear to be an appreciable performance difference between GAIL with sub-optimal demonstrations and M-GAIL experimentally. Thus, I do not believe I need to revise my score, as the difference between this work and previous work for this version of the paper is too minor. "}, "signatures": ["ICLR.cc/2019/Conference/Paper575/AnonReviewer4"], "readers": ["everyone"], "nonreaders": ["ICLR.cc/2019/Conference/Paper575/Reviewers/Unsubmitted"], "writers": ["ICLR.cc/2019/Conference/Paper575/AnonReviewer4", "ICLR.cc/2019/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations", "abstract": "Imitation learning aims to learn an optimal policy from expert demonstrations and its recent combination with deep learning has shown impressive performance. However, collecting a large number of expert demonstrations for deep learning is time-consuming and requires much expert effort. In this paper, we propose a method to improve generative adversarial imitation learning by using additional information from non-expert demonstrations which are easier to obtain. The key idea of our method is to perform multiclass classification to learn discriminator functions where non-expert demonstrations are regarded as being drawn from an extra class. Experiments in continuous control tasks demonstrate that our method learns better policies than the generative adversarial imitation learning baseline when the number of expert demonstrations is small.", "keywords": ["Imitation learning", "Generative adversarial imitation learning"], "authorids": ["voot.tangkaratt@riken.jp", "sugi@k.u-tokyo.ac.jp"], "authors": ["Voot Tangkaratt", "Masashi Sugiyama"], "TL;DR": "We improve GAIL by learning discriminators using multiclass classification with non-expert regarded as an extra class.", "pdf": "/pdf/3bd7072ceff083939e4740be0cd7f1f2ef0dffdc.pdf", "paperhash": "tangkaratt|improving_generative_adversarial_imitation_learning_with_nonexpert_demonstrations", "_bibtex": "@misc{\ntangkaratt2019improving,\ntitle={Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations},\nauthor={Voot Tangkaratt and Masashi Sugiyama},\nyear={2019},\nurl={https://openreview.net/forum?id=BJl65sA9tm},\n}"}, "tags": [], "invitation": {"id": "ICLR.cc/2019/Conference/-/Paper575/Official_Comment", "rdate": null, "ddate": null, "expdate": null, "duedate": null, "tmdate": 1543621614845, "tddate": null, "super": null, "final": null, "reply": {"forum": "BJl65sA9tm", "replyto": null, "readers": {"description": "Select all user groups that should be able to read this comment.", "value-dropdown-hierarchy": ["everyone", "ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference/Paper575/Reviewers", "ICLR.cc/2019/Conference/Paper575/Area_Chairs", "ICLR.cc/2019/Conference/Program_Chairs"]}, "nonreaders": {"values": ["ICLR.cc/2019/Conference/Paper575/Reviewers/Unsubmitted"]}, "signatures": {"description": "", "values-regex": "ICLR.cc/2019/Conference/Paper575/AnonReviewer[0-9]+|ICLR.cc/2019/Conference/Paper575/Authors|ICLR.cc/2019/Conference/Paper575/Area_Chair[0-9]+|ICLR.cc/2019/Conference/Program_Chairs"}, "writers": {"description": "Users that may modify this record.", "values-copied": ["ICLR.cc/2019/Conference", "{signatures}"]}, "content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters).", "required": true}}}, "signatures": ["ICLR.cc/2019/Conference"], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2019/Conference/Paper575/Reviewers", "ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference/Paper575/Area_Chairs", "ICLR.cc/2019/Conference/Program_Chairs"], "noninvitees": [], "writers": ["ICLR.cc/2019/Conference"], "multiReply": true, "taskCompletionCount": null, "transform": null, "cdate": 1543621614845}}}, {"id": "BygodKhSAQ", "original": null, "number": 7, "cdate": 1542994290610, "ddate": null, "tcdate": 1542994290610, "tmdate": 1542994290610, "tddate": null, "forum": "BJl65sA9tm", "replyto": "rklN7J19hQ", "invitation": "ICLR.cc/2019/Conference/-/Paper575/Official_Comment", "content": {"title": "Reply to reviewer 3's comment", "comment": "Thank you for the comments. Our replies to the comments and questions of reviewer 3 are given below.\n\n1. The general problem setting is interesting, but I think it is of rather little significance, because I do not see many clear applications.\n\n-We would like to argue that there are many applications, including robotics, where non-expert demonstrations are abundance despite them being expensive to obtain. For instance, kinesthetic teaching is often used to gather demonstrations from a human teacher in robotics. However, it is common that the teacher does not know physical constraints of the robot well initially and the teacher needs some time to be familiar with the robot. During this time, teacher\u2019s demonstrations, which have a large margin of error and are sub-optimal, would be throwaway for traditional IL methods. The expert demonstrations are collected only when the teacher is well familiar with the robot and can perform the task with a minimal error (Small errors and noises in demonstrations can be coped with by probabilistic formulation of maximum entropy IRL and GAIL, as mentioned by reviewer 4.).\n\nWhile our experiments with simulated robots are not exactly the same as this example, we believe that they can serve as benchmarks to show the benefit of using non-expert demonstrations that are generally ignored. Indeed, evaluations on real-world applications are needed to firmly demonstrate the practical usefulness of this setting. However, such evaluations are beyond the scope of the paper which is to introduce the problem setting and propose a simple yet efficient approach to solve it. \n\n2. I think the paper would profit a lot from having an experiment where the importance of making use of non-expert data becomes evident.\n\n- We agree, and we have included a new set of experiment with smaller numbers of samples available. The new results show that methods that use the non-expert dataset, including our method and the two new baselines, significantly outperform GAIL both in terms of average performance and final performance. \n\n3. However, non-expert data is typically not cheaper than policy roll-outs.\n\n- While the complexity of collecting non-expert demonstrations and policy roll-outs are similar, non-expert demonstrations are more informative than roll-outs from a poor policy such as an initial policy. Moreover, collecting data by a non-expert human is more preferable since non-expert is more likely to execute safe actions while the agent may execute hazardous actions due to exploration noise. \n\n4. The experiments also show only slight benefits, especially when comparing the final performance\n\n- We agree that the experiment setup seems unfair to GAIL since it uses less samples. We expect that the two new baselines make the evaluation of M-GAIL fairer. However, in terms of the total sample size, the agent collects samples of size 10 million in total while the non-expert dataset is only of size 0.1 million which is relatively small compared to 10 million. \n\nWe also agree that final performance is important for evaluation. In the revision, we report final performance in Table 2 and Table 4. The results for the small sample setting in Table 2 show significant improvement when using non-expert demonstrations. For the large sample setting, there is no significant difference in the final performance in Table 4. This is as expected since GAIL eventually learns a good policy after it collects enough samples in this setting.\n\n3. It would also be interesting to show, whether we can benefit from using the policy roll-outs of previous iterations as non-expert data for the current iteration\n\n- The suggested self-improving idea is very interesting, and we discuss this suggestion in the conclusion. However, we think that this approach can be highly unstable since the two classes of agent\u2019s trajectories are changing in each iteration. \n\n4. The main weakness of the paper is, that the novelty seems marginal. \n\n- While simple, the modification from binary classification to multiclass classification is very important to ensure that the agent learn the expert policy while utilizing non-expert dataset. Also, we would like to emphasize that one of our contribution is to demonstrate that universum learning is useful in IL and generative adversarial learning. To the best of our knowledge, this was never considered before despite successes of semi-supervised learning in IL and generative adversarial learning.\n\n5. The point of section 4.4. and the related appendix A2.\n\n-The point of Section 4.4 is to show that the proposed method does not perform IRL and only approximates an IRL solution. We believe that this negative result will motivate developing deep IRL methods for the proposed problem setting. However, we agree that this result does not play an important role in the paper. For better clarity, we move Section 4.4 to appendix and discuss the relation only in the conclusion.\n"}, "signatures": ["ICLR.cc/2019/Conference/Paper575/Authors"], "readers": ["everyone"], "nonreaders": ["ICLR.cc/2019/Conference/Paper575/Reviewers/Unsubmitted"], "writers": ["ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations", "abstract": "Imitation learning aims to learn an optimal policy from expert demonstrations and its recent combination with deep learning has shown impressive performance. However, collecting a large number of expert demonstrations for deep learning is time-consuming and requires much expert effort. In this paper, we propose a method to improve generative adversarial imitation learning by using additional information from non-expert demonstrations which are easier to obtain. The key idea of our method is to perform multiclass classification to learn discriminator functions where non-expert demonstrations are regarded as being drawn from an extra class. Experiments in continuous control tasks demonstrate that our method learns better policies than the generative adversarial imitation learning baseline when the number of expert demonstrations is small.", "keywords": ["Imitation learning", "Generative adversarial imitation learning"], "authorids": ["voot.tangkaratt@riken.jp", "sugi@k.u-tokyo.ac.jp"], "authors": ["Voot Tangkaratt", "Masashi Sugiyama"], "TL;DR": "We improve GAIL by learning discriminators using multiclass classification with non-expert regarded as an extra class.", "pdf": "/pdf/3bd7072ceff083939e4740be0cd7f1f2ef0dffdc.pdf", "paperhash": "tangkaratt|improving_generative_adversarial_imitation_learning_with_nonexpert_demonstrations", "_bibtex": "@misc{\ntangkaratt2019improving,\ntitle={Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations},\nauthor={Voot Tangkaratt and Masashi Sugiyama},\nyear={2019},\nurl={https://openreview.net/forum?id=BJl65sA9tm},\n}"}, "tags": [], "invitation": {"id": "ICLR.cc/2019/Conference/-/Paper575/Official_Comment", "rdate": null, "ddate": null, "expdate": null, "duedate": null, "tmdate": 1543621614845, "tddate": null, "super": null, "final": null, "reply": {"forum": "BJl65sA9tm", "replyto": null, "readers": {"description": "Select all user groups that should be able to read this comment.", "value-dropdown-hierarchy": ["everyone", "ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference/Paper575/Reviewers", "ICLR.cc/2019/Conference/Paper575/Area_Chairs", "ICLR.cc/2019/Conference/Program_Chairs"]}, "nonreaders": {"values": ["ICLR.cc/2019/Conference/Paper575/Reviewers/Unsubmitted"]}, "signatures": {"description": "", "values-regex": "ICLR.cc/2019/Conference/Paper575/AnonReviewer[0-9]+|ICLR.cc/2019/Conference/Paper575/Authors|ICLR.cc/2019/Conference/Paper575/Area_Chair[0-9]+|ICLR.cc/2019/Conference/Program_Chairs"}, "writers": {"description": "Users that may modify this record.", "values-copied": ["ICLR.cc/2019/Conference", "{signatures}"]}, "content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters).", "required": true}}}, "signatures": ["ICLR.cc/2019/Conference"], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2019/Conference/Paper575/Reviewers", "ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference/Paper575/Area_Chairs", "ICLR.cc/2019/Conference/Program_Chairs"], "noninvitees": [], "writers": ["ICLR.cc/2019/Conference"], "multiReply": true, "taskCompletionCount": null, "transform": null, "cdate": 1543621614845}}}, {"id": "rJeGdLhHC7", "original": null, "number": 6, "cdate": 1542993514046, "ddate": null, "tcdate": 1542993514046, "tmdate": 1542993514046, "tddate": null, "forum": "BJl65sA9tm", "replyto": "S1g02-Kc3X", "invitation": "ICLR.cc/2019/Conference/-/Paper575/Official_Comment", "content": {"title": "Reply to reviewer 2's comment", "comment": "Thank you for the comments. Our replies to comments and questions of reviewer 2 are given below.\n\n1. Why can't non-expert trajectories be considered as an initial set of agent trajectories? If multiclass is indeed required, it would be nice to see a comparison of what happens when non experts trajectories were just considered agents.\n\n- It is possible to include non-expert trajectories into agent trajectories and perform GAIL with binary classification. However, as mentioned in the common reply, this approach learns a mixture policy and does not perform IL. It also does not provide much improvement over GAIL in our experiments.\n\nAn alternative approach is to use non-expert trajectories for off-policy update in policy learning. However, this is not applicable since we do not know the non-expert policy, so we cannot compute importance weight to correct the bias.\n\n2. In table 1 we see that standard errors between the new method and gail are comparable, where does such a huge diff in var come from in Figure 1? \n\n- Previously in Table 1, we treated test return in each iteration of each trail as an individual sample. This makes the standard error very small since it is computed from a very large number of samples. We correct this misleading standard error in the revision and treat a total return of each trial as one sample. However, using only 5 samples (from 5 trials) we cannot evaluate statistical significance well. Instead, we consider two best methods in terms of the mean value in the new tables.\n\n3. the sensitivity of the algorithm to lambda. how would one go setting it? In the experiments it seems that authors just try two different values (0.1 and 0.5) but i assume this really should be a hyperparameter search for this. Is lambda dependent on the number of expert and non expert demonstrations that are available?\n\n- An optimal \\lambda should depend on number of expert and non-expert demonstrations, similarly to a class prior in standard classification. However, it is not exactly a class prior since G_{\\phi} also contains \\lambda. Currently, we treat \\lambda as a hyper-parameter specified by the user. In the revision, we include \\lambda=0.01 in the experiments to better investigate the sensitivity. Developing a more principal approach (e.g., a computationally efficient online cross-validation procedure) to determine the optimal value of \\lambda is left for future work.\n"}, "signatures": ["ICLR.cc/2019/Conference/Paper575/Authors"], "readers": ["everyone"], "nonreaders": ["ICLR.cc/2019/Conference/Paper575/Reviewers/Unsubmitted"], "writers": ["ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations", "abstract": "Imitation learning aims to learn an optimal policy from expert demonstrations and its recent combination with deep learning has shown impressive performance. However, collecting a large number of expert demonstrations for deep learning is time-consuming and requires much expert effort. In this paper, we propose a method to improve generative adversarial imitation learning by using additional information from non-expert demonstrations which are easier to obtain. The key idea of our method is to perform multiclass classification to learn discriminator functions where non-expert demonstrations are regarded as being drawn from an extra class. Experiments in continuous control tasks demonstrate that our method learns better policies than the generative adversarial imitation learning baseline when the number of expert demonstrations is small.", "keywords": ["Imitation learning", "Generative adversarial imitation learning"], "authorids": ["voot.tangkaratt@riken.jp", "sugi@k.u-tokyo.ac.jp"], "authors": ["Voot Tangkaratt", "Masashi Sugiyama"], "TL;DR": "We improve GAIL by learning discriminators using multiclass classification with non-expert regarded as an extra class.", "pdf": "/pdf/3bd7072ceff083939e4740be0cd7f1f2ef0dffdc.pdf", "paperhash": "tangkaratt|improving_generative_adversarial_imitation_learning_with_nonexpert_demonstrations", "_bibtex": "@misc{\ntangkaratt2019improving,\ntitle={Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations},\nauthor={Voot Tangkaratt and Masashi Sugiyama},\nyear={2019},\nurl={https://openreview.net/forum?id=BJl65sA9tm},\n}"}, "tags": [], "invitation": {"id": "ICLR.cc/2019/Conference/-/Paper575/Official_Comment", "rdate": null, "ddate": null, "expdate": null, "duedate": null, "tmdate": 1543621614845, "tddate": null, "super": null, "final": null, "reply": {"forum": "BJl65sA9tm", "replyto": null, "readers": {"description": "Select all user groups that should be able to read this comment.", "value-dropdown-hierarchy": ["everyone", "ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference/Paper575/Reviewers", "ICLR.cc/2019/Conference/Paper575/Area_Chairs", "ICLR.cc/2019/Conference/Program_Chairs"]}, "nonreaders": {"values": ["ICLR.cc/2019/Conference/Paper575/Reviewers/Unsubmitted"]}, "signatures": {"description": "", "values-regex": "ICLR.cc/2019/Conference/Paper575/AnonReviewer[0-9]+|ICLR.cc/2019/Conference/Paper575/Authors|ICLR.cc/2019/Conference/Paper575/Area_Chair[0-9]+|ICLR.cc/2019/Conference/Program_Chairs"}, "writers": {"description": "Users that may modify this record.", "values-copied": ["ICLR.cc/2019/Conference", "{signatures}"]}, "content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters).", "required": true}}}, "signatures": ["ICLR.cc/2019/Conference"], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2019/Conference/Paper575/Reviewers", "ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference/Paper575/Area_Chairs", "ICLR.cc/2019/Conference/Program_Chairs"], "noninvitees": [], "writers": ["ICLR.cc/2019/Conference"], "multiReply": true, "taskCompletionCount": null, "transform": null, "cdate": 1543621614845}}}, {"id": "r1eMyU2rR7", "original": null, "number": 5, "cdate": 1542993370092, "ddate": null, "tcdate": 1542993370092, "tmdate": 1542993370092, "tddate": null, "forum": "BJl65sA9tm", "replyto": "BygZOLGGaQ", "invitation": "ICLR.cc/2019/Conference/-/Paper575/Official_Comment", "content": {"title": "Reply to reviewer 4's comment", "comment": "Thank you for the comments. Our replies to comments and questions of reviewer 4 are given below.\n\n1. The proposed algorithm seems equivalent to adding the \"sub-optimal\" demonstrations to the expert demonstrations, but down-weighting each sub-optimal demonstration be a factor of \\lambda. [\u2026] The existing MaxEnt frameworks seem to handle the notion of sub-optimality proposed in this paper just as well, interpreting the \"sub-optimal\" demonstrations as low-probability expert demonstrations. [\u2026] If this equivalence is true, I would encourage the authors to include this discussion in the main paper, and if not, discuss the differences and possibly compare against this simple strategy as a baseline.\n\n- A direct application of maximum entropy IRL is not appropriate in our setting since we assume that we have a much larger number of non-expert demonstrations. By mixing the two datasets, maximum entropy IRL treats expert demonstrations as low probability ones instead. To avoid this, it is necessary to down-weight non-expert demonstrations by a weight \\lambda. We call this method U-GAIL in the revision. \n\nIn U-GAIL, the agent learns a mixture policy where the mixture coefficient is controlled by \\lambda. However, by using binary classification, or equivalently one reward function in the IRL view, the agent cannot distinguish between learning signals from expert and that from non-expert. As a result, we cannot choose to learn only the expert policy from an already learned discriminator. Using a third class avoids this issue since learning signals from expert and non-expert are separately given by different discriminators. For these reasons, a third class is necessary to perform IL using non-expert demonstrations, and our method is not equivalent to adding down-weighted non-expert demonstrations to expert demonstrations and then performing GAIL.\n\nWhile U-GAIL does not perform IL, our experiment in Section 6 shows that learning a mixture policy can be beneficial when non-expert is not too poor. To make use of this benefit, Section 4.4 considers a simple extension of M-GAIL that learns also a mixture policy but allows using different weights for the discriminator and policy learning steps.\n\n2. I am curious if the authors tried annealing the \\lambda term from 1.0 to 0.0, as lambda=1.0 is likely easier to learn from, but lambda=0.0 would have better asymptotic performance.\n\n- We have previously tried annealing \\lambda for our method and we found that it is highly unstable. This is likely because changing \\lambda also changes the optimal discriminator which is also coupling with changes in the agent\u2019s trajectory distribution. Moreover, it is difficult to use the same annealing schedule for all tasks. For this reason, we keep \\lambda fix which already gives good empirical performance.\n"}, "signatures": ["ICLR.cc/2019/Conference/Paper575/Authors"], "readers": ["everyone"], "nonreaders": ["ICLR.cc/2019/Conference/Paper575/Reviewers/Unsubmitted"], "writers": ["ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations", "abstract": "Imitation learning aims to learn an optimal policy from expert demonstrations and its recent combination with deep learning has shown impressive performance. However, collecting a large number of expert demonstrations for deep learning is time-consuming and requires much expert effort. In this paper, we propose a method to improve generative adversarial imitation learning by using additional information from non-expert demonstrations which are easier to obtain. The key idea of our method is to perform multiclass classification to learn discriminator functions where non-expert demonstrations are regarded as being drawn from an extra class. Experiments in continuous control tasks demonstrate that our method learns better policies than the generative adversarial imitation learning baseline when the number of expert demonstrations is small.", "keywords": ["Imitation learning", "Generative adversarial imitation learning"], "authorids": ["voot.tangkaratt@riken.jp", "sugi@k.u-tokyo.ac.jp"], "authors": ["Voot Tangkaratt", "Masashi Sugiyama"], "TL;DR": "We improve GAIL by learning discriminators using multiclass classification with non-expert regarded as an extra class.", "pdf": "/pdf/3bd7072ceff083939e4740be0cd7f1f2ef0dffdc.pdf", "paperhash": "tangkaratt|improving_generative_adversarial_imitation_learning_with_nonexpert_demonstrations", "_bibtex": "@misc{\ntangkaratt2019improving,\ntitle={Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations},\nauthor={Voot Tangkaratt and Masashi Sugiyama},\nyear={2019},\nurl={https://openreview.net/forum?id=BJl65sA9tm},\n}"}, "tags": [], "invitation": {"id": "ICLR.cc/2019/Conference/-/Paper575/Official_Comment", "rdate": null, "ddate": null, "expdate": null, "duedate": null, "tmdate": 1543621614845, "tddate": null, "super": null, "final": null, "reply": {"forum": "BJl65sA9tm", "replyto": null, "readers": {"description": "Select all user groups that should be able to read this comment.", "value-dropdown-hierarchy": ["everyone", "ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference/Paper575/Reviewers", "ICLR.cc/2019/Conference/Paper575/Area_Chairs", "ICLR.cc/2019/Conference/Program_Chairs"]}, "nonreaders": {"values": ["ICLR.cc/2019/Conference/Paper575/Reviewers/Unsubmitted"]}, "signatures": {"description": "", "values-regex": "ICLR.cc/2019/Conference/Paper575/AnonReviewer[0-9]+|ICLR.cc/2019/Conference/Paper575/Authors|ICLR.cc/2019/Conference/Paper575/Area_Chair[0-9]+|ICLR.cc/2019/Conference/Program_Chairs"}, "writers": {"description": "Users that may modify this record.", "values-copied": ["ICLR.cc/2019/Conference", "{signatures}"]}, "content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters).", "required": true}}}, "signatures": ["ICLR.cc/2019/Conference"], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2019/Conference/Paper575/Reviewers", "ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference/Paper575/Area_Chairs", "ICLR.cc/2019/Conference/Program_Chairs"], "noninvitees": [], "writers": ["ICLR.cc/2019/Conference"], "multiReply": true, "taskCompletionCount": null, "transform": null, "cdate": 1543621614845}}}, {"id": "rklDzShHRm", "original": null, "number": 4, "cdate": 1542993166871, "ddate": null, "tcdate": 1542993166871, "tmdate": 1542993166871, "tddate": null, "forum": "BJl65sA9tm", "replyto": "HJl1UZlN6Q", "invitation": "ICLR.cc/2019/Conference/-/Paper575/Official_Comment", "content": {"title": "Reply to reviewer 1's comment", "comment": "Thank you for the comments. Our replies to the comments and questions of reviewer 1 are given below.\n\n1. It is unclear to me why the experiments did not attempt to supply the nonexpert demonstrations to GAIL too - one could e.g. have naively pooled the nonexpert demonstration into one of GAIL's binary classes, \"expert\" or \"policy\".\n- We have considered the suggested approaches before. However, we did not pursue them since in order to learn the expert policy they require annealing the weight parameter and eventually ignoring non-expert data. However, we agree that these approaches should have been discussed and evaluated in the paper. In the revision, we provide detailed discussions and evaluations of these approaches.\n\n2. The method also requires the additional parameter lambda which affects performance in the experiments - it is not clear how to set it in practice, does e.g. cross-validation etc. need to be used? It would be useful to know more about sensitivity to lambda, experiments only consider two values. \n- Hyper-parameter selection procedure such as cross-validation (CV) may be used to choose \\lambda based on classification accuracy. However, the agent\u2019s trajectory distribution is always changing and the optimal \\lambda should be different between iterations. Since performing CV in every iterations is costly, we treat \\lambda as a hyper-parameter specified by the user. To better investigate the sensitivity, we include \\lambda=0.01 in the experiments. \n\n3. In the methodological derivation, it was unclear to me why only one parameter lambda is used to control class balance, why not two parameters controlling prevalence of the expert class, policy class, and nonexpert class?\n- It is possible to use additional weights to balance the three classes since they only change weights of each occupancy measure in the JS divergence. We decide to have only the weight parameter for the non-expert class since the standard GAIL assumes the same class balance between expert and agent classes.\n\n4. In proposition 1 the fact that the bias vanishes when lambda=0 seems trivial because eq. 9 reduces to the first term on the right hand side.\n- Proposition 1 is a trivial result based on that of Fu et al. Our intentions are to show that M-GAIL only finds an approximate IRL solution and that further study is needed to perform IRL in our setting. To make this clearer, we only briefly mention the relation to IRL in the conclusion and move detailed discussions to appendix.\n\n5. In eq. 5 it's not quite right to call the right-hand side a loglikelihood. Loglikelihoods should be sums over observations of each class (thus emphasizing classes with more data) whereas here each term is an expectation - or do you assume the number of samples corresponding to each expectation term is equal?\n- Thank you for pointing out this mistake. We do not specifically assume equal sample sizes. We correct the terminology and use the term objective instead of log-likelihood in the revision.\n"}, "signatures": ["ICLR.cc/2019/Conference/Paper575/Authors"], "readers": ["everyone"], "nonreaders": ["ICLR.cc/2019/Conference/Paper575/Reviewers/Unsubmitted"], "writers": ["ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations", "abstract": "Imitation learning aims to learn an optimal policy from expert demonstrations and its recent combination with deep learning has shown impressive performance. However, collecting a large number of expert demonstrations for deep learning is time-consuming and requires much expert effort. In this paper, we propose a method to improve generative adversarial imitation learning by using additional information from non-expert demonstrations which are easier to obtain. The key idea of our method is to perform multiclass classification to learn discriminator functions where non-expert demonstrations are regarded as being drawn from an extra class. Experiments in continuous control tasks demonstrate that our method learns better policies than the generative adversarial imitation learning baseline when the number of expert demonstrations is small.", "keywords": ["Imitation learning", "Generative adversarial imitation learning"], "authorids": ["voot.tangkaratt@riken.jp", "sugi@k.u-tokyo.ac.jp"], "authors": ["Voot Tangkaratt", "Masashi Sugiyama"], "TL;DR": "We improve GAIL by learning discriminators using multiclass classification with non-expert regarded as an extra class.", "pdf": "/pdf/3bd7072ceff083939e4740be0cd7f1f2ef0dffdc.pdf", "paperhash": "tangkaratt|improving_generative_adversarial_imitation_learning_with_nonexpert_demonstrations", "_bibtex": "@misc{\ntangkaratt2019improving,\ntitle={Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations},\nauthor={Voot Tangkaratt and Masashi Sugiyama},\nyear={2019},\nurl={https://openreview.net/forum?id=BJl65sA9tm},\n}"}, "tags": [], "invitation": {"id": "ICLR.cc/2019/Conference/-/Paper575/Official_Comment", "rdate": null, "ddate": null, "expdate": null, "duedate": null, "tmdate": 1543621614845, "tddate": null, "super": null, "final": null, "reply": {"forum": "BJl65sA9tm", "replyto": null, "readers": {"description": "Select all user groups that should be able to read this comment.", "value-dropdown-hierarchy": ["everyone", "ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference/Paper575/Reviewers", "ICLR.cc/2019/Conference/Paper575/Area_Chairs", "ICLR.cc/2019/Conference/Program_Chairs"]}, "nonreaders": {"values": ["ICLR.cc/2019/Conference/Paper575/Reviewers/Unsubmitted"]}, "signatures": {"description": "", "values-regex": "ICLR.cc/2019/Conference/Paper575/AnonReviewer[0-9]+|ICLR.cc/2019/Conference/Paper575/Authors|ICLR.cc/2019/Conference/Paper575/Area_Chair[0-9]+|ICLR.cc/2019/Conference/Program_Chairs"}, "writers": {"description": "Users that may modify this record.", "values-copied": ["ICLR.cc/2019/Conference", "{signatures}"]}, "content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters).", "required": true}}}, "signatures": ["ICLR.cc/2019/Conference"], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2019/Conference/Paper575/Reviewers", "ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference/Paper575/Area_Chairs", "ICLR.cc/2019/Conference/Program_Chairs"], "noninvitees": [], "writers": ["ICLR.cc/2019/Conference"], "multiReply": true, "taskCompletionCount": null, "transform": null, "cdate": 1543621614845}}}, {"id": "rklOMN2SRm", "original": null, "number": 3, "cdate": 1542992912048, "ddate": null, "tcdate": 1542992912048, "tmdate": 1542992912048, "tddate": null, "forum": "BJl65sA9tm", "replyto": "BJl65sA9tm", "invitation": "ICLR.cc/2019/Conference/-/Paper575/Official_Comment", "content": {"title": "Changes made in the revision", "comment": "Dear reviewers,\n\nWe thank the reviewers for insightful comments and suggestions. Our replies to reviewers\u2019 comments and questions will be posted separately. In this comment, we explain changes in the revision that should address concerns of the reviewers.\n\n---Two GAIL extensions in Section 5 that mix the non-expert dataset to the expert or agent datasets.---\nCommon major concerns of the reviewers are the importance of using the third class and the lack of comparison against GAIL extensions that perform binary classification with non-expert data. To clarify these, we add a new section (Section 5) titled \u201cDiscussion on Binary Classification with Non-expert Data\u201d that discusses two extensions of GAIL. In the first extension which we call U-GAIL, the non-expert dataset is mixed with the expert dataset and is down-weighted by \\lambda. This method is equivalent to the method suggested by reviewer 1 and 4. An important issue of this method is that it learns a mixture of expert and non-expert policies. Thus, it does not learn only the expert policy which is the goal of IL. Our experiments show that this method works well when non-expert policy is not too different from the expert policy but works poorly otherwise. \n\nFor the second extension which we call V-GAIL, the non-expert dataset is mixed with the agent (current policy) dataset and is down-weighted by \\lambda. This method is equivalent to the method suggested by reviewer 1 and 2. Similarly to U-GAIL, this method does not perform IL since it learns a policy mixture of expert and non-expert policies. Moreover, it requires an additional constraint to ensure non-negativity of the resulting occupancy measure. Our experiments show that this method does not provide much improvement over GAIL. \n\nThe issue of these two extensions emphases the novelty and importance of performing multiclass classification with non-expert demonstrations in our method. \n\nWe also evaluate a simple extension of our method where we learn a policy mixture, similarly to U-GAIL. We call this method mixture M-GAIL (MM-GAIL) and discuss it in Section 4.4. Unlike U-GAIL, we can specify a mixture coefficient (\\omega) during policy learning that can be different from \\lambda which is used during discriminator learning. \n\n---New experimental setting in Section 6 with smaller numbers of expert demonstrations.---\nAnother common concern of the reviewers is that non-expert dataset seems to provide only marginal improvement. To better demonstrate the usefulness of our method, we perform additional experiments with smaller numbers of expert demonstrations (N=100, 300, 500) and agent\u2019s transition samples in each iteration (K=1000). The new results show that non-expert demonstrations significantly improve performance when compared to GAIL. This additional experiment can be found in the first half of Section 6. The previous experiment with N=1000, 10000 and K=2000 can be found in the second half of Section 6.\n\nWe also evaluate performance with \\lambda=0.01 to investigate the sensitivity against \\lambda of each method. The results in Figures 4 to 11 in the appendix show that M-GAIL is less sensitive to \\lambda when compare to U-GAIL. This is likely because \\lambda directly affects both the discriminator and the optimal policy (i.e., the mixture policy) in U-GAIL, while it only affects the discriminator in M-GAIL. \n"}, "signatures": ["ICLR.cc/2019/Conference/Paper575/Authors"], "readers": ["everyone"], "nonreaders": ["ICLR.cc/2019/Conference/Paper575/Reviewers/Unsubmitted"], "writers": ["ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations", "abstract": "Imitation learning aims to learn an optimal policy from expert demonstrations and its recent combination with deep learning has shown impressive performance. However, collecting a large number of expert demonstrations for deep learning is time-consuming and requires much expert effort. In this paper, we propose a method to improve generative adversarial imitation learning by using additional information from non-expert demonstrations which are easier to obtain. The key idea of our method is to perform multiclass classification to learn discriminator functions where non-expert demonstrations are regarded as being drawn from an extra class. Experiments in continuous control tasks demonstrate that our method learns better policies than the generative adversarial imitation learning baseline when the number of expert demonstrations is small.", "keywords": ["Imitation learning", "Generative adversarial imitation learning"], "authorids": ["voot.tangkaratt@riken.jp", "sugi@k.u-tokyo.ac.jp"], "authors": ["Voot Tangkaratt", "Masashi Sugiyama"], "TL;DR": "We improve GAIL by learning discriminators using multiclass classification with non-expert regarded as an extra class.", "pdf": "/pdf/3bd7072ceff083939e4740be0cd7f1f2ef0dffdc.pdf", "paperhash": "tangkaratt|improving_generative_adversarial_imitation_learning_with_nonexpert_demonstrations", "_bibtex": "@misc{\ntangkaratt2019improving,\ntitle={Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations},\nauthor={Voot Tangkaratt and Masashi Sugiyama},\nyear={2019},\nurl={https://openreview.net/forum?id=BJl65sA9tm},\n}"}, "tags": [], "invitation": {"id": "ICLR.cc/2019/Conference/-/Paper575/Official_Comment", "rdate": null, "ddate": null, "expdate": null, "duedate": null, "tmdate": 1543621614845, "tddate": null, "super": null, "final": null, "reply": {"forum": "BJl65sA9tm", "replyto": null, "readers": {"description": "Select all user groups that should be able to read this comment.", "value-dropdown-hierarchy": ["everyone", "ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference/Paper575/Reviewers", "ICLR.cc/2019/Conference/Paper575/Area_Chairs", "ICLR.cc/2019/Conference/Program_Chairs"]}, "nonreaders": {"values": ["ICLR.cc/2019/Conference/Paper575/Reviewers/Unsubmitted"]}, "signatures": {"description": "", "values-regex": "ICLR.cc/2019/Conference/Paper575/AnonReviewer[0-9]+|ICLR.cc/2019/Conference/Paper575/Authors|ICLR.cc/2019/Conference/Paper575/Area_Chair[0-9]+|ICLR.cc/2019/Conference/Program_Chairs"}, "writers": {"description": "Users that may modify this record.", "values-copied": ["ICLR.cc/2019/Conference", "{signatures}"]}, "content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters).", "required": true}}}, "signatures": ["ICLR.cc/2019/Conference"], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2019/Conference/Paper575/Reviewers", "ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference/Paper575/Area_Chairs", "ICLR.cc/2019/Conference/Program_Chairs"], "noninvitees": [], "writers": ["ICLR.cc/2019/Conference"], "multiReply": true, "taskCompletionCount": null, "transform": null, "cdate": 1543621614845}}}, {"id": "HJl1UZlN6Q", "original": null, "number": 1, "cdate": 1541828934820, "ddate": null, "tcdate": 1541828934820, "tmdate": 1541828934820, "tddate": null, "forum": "BJl65sA9tm", "replyto": "rJxYAkx46m", "invitation": "ICLR.cc/2019/Conference/-/Paper575/Official_Comment", "content": {"title": "Correction to broken sentence", "comment": "The sentence \"This is especially concerning since bett\" was missing some words, it should have read as follows: \"This is especially concerning since best performance in M-GAIL depends on quality of the non-expert demonstrations, hence GAIL could also benefit from them under some quality settings.\""}, "signatures": ["ICLR.cc/2019/Conference/Paper575/AnonReviewer1"], "readers": ["everyone"], "nonreaders": ["ICLR.cc/2019/Conference/Paper575/Reviewers/Unsubmitted"], "writers": ["ICLR.cc/2019/Conference/Paper575/AnonReviewer1", "ICLR.cc/2019/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations", "abstract": "Imitation learning aims to learn an optimal policy from expert demonstrations and its recent combination with deep learning has shown impressive performance. However, collecting a large number of expert demonstrations for deep learning is time-consuming and requires much expert effort. In this paper, we propose a method to improve generative adversarial imitation learning by using additional information from non-expert demonstrations which are easier to obtain. The key idea of our method is to perform multiclass classification to learn discriminator functions where non-expert demonstrations are regarded as being drawn from an extra class. Experiments in continuous control tasks demonstrate that our method learns better policies than the generative adversarial imitation learning baseline when the number of expert demonstrations is small.", "keywords": ["Imitation learning", "Generative adversarial imitation learning"], "authorids": ["voot.tangkaratt@riken.jp", "sugi@k.u-tokyo.ac.jp"], "authors": ["Voot Tangkaratt", "Masashi Sugiyama"], "TL;DR": "We improve GAIL by learning discriminators using multiclass classification with non-expert regarded as an extra class.", "pdf": "/pdf/3bd7072ceff083939e4740be0cd7f1f2ef0dffdc.pdf", "paperhash": "tangkaratt|improving_generative_adversarial_imitation_learning_with_nonexpert_demonstrations", "_bibtex": "@misc{\ntangkaratt2019improving,\ntitle={Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations},\nauthor={Voot Tangkaratt and Masashi Sugiyama},\nyear={2019},\nurl={https://openreview.net/forum?id=BJl65sA9tm},\n}"}, "tags": [], "invitation": {"id": "ICLR.cc/2019/Conference/-/Paper575/Official_Comment", "rdate": null, "ddate": null, "expdate": null, "duedate": null, "tmdate": 1543621614845, "tddate": null, "super": null, "final": null, "reply": {"forum": "BJl65sA9tm", "replyto": null, "readers": {"description": "Select all user groups that should be able to read this comment.", "value-dropdown-hierarchy": ["everyone", "ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference/Paper575/Reviewers", "ICLR.cc/2019/Conference/Paper575/Area_Chairs", "ICLR.cc/2019/Conference/Program_Chairs"]}, "nonreaders": {"values": ["ICLR.cc/2019/Conference/Paper575/Reviewers/Unsubmitted"]}, "signatures": {"description": "", "values-regex": "ICLR.cc/2019/Conference/Paper575/AnonReviewer[0-9]+|ICLR.cc/2019/Conference/Paper575/Authors|ICLR.cc/2019/Conference/Paper575/Area_Chair[0-9]+|ICLR.cc/2019/Conference/Program_Chairs"}, "writers": {"description": "Users that may modify this record.", "values-copied": ["ICLR.cc/2019/Conference", "{signatures}"]}, "content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters).", "required": true}}}, "signatures": ["ICLR.cc/2019/Conference"], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2019/Conference/Paper575/Reviewers", "ICLR.cc/2019/Conference/Paper575/Authors", "ICLR.cc/2019/Conference/Paper575/Area_Chairs", "ICLR.cc/2019/Conference/Program_Chairs"], "noninvitees": [], "writers": ["ICLR.cc/2019/Conference"], "multiReply": true, "taskCompletionCount": null, "transform": null, "cdate": 1543621614845}}}, {"id": "rJxYAkx46m", "original": null, "number": 4, "cdate": 1541828561513, "ddate": null, "tcdate": 1541828561513, "tmdate": 1541828561513, "tddate": null, "forum": "BJl65sA9tm", "replyto": "BJl65sA9tm", "invitation": "ICLR.cc/2019/Conference/-/Paper575/Official_Review", "content": {"title": "Interesting idea but experimental comparison may not be fair, also sensitivity to lambda parameter is unclear", "review": "Description:\n\nThis paper presents a variant of imitation-based reinforcement learning, when in addition to example trajectories of an expert , example trajectories of non-experts are available.\n\nIn brief, the method is a variant of the GAIL method for adversarial training. In GAIL, the policy is optimized to minimize the ability to discriminate (classify) two classes: trajectories of the expert vs. trajectories from the policy, where the discrimination ability is measured by a neural network discriminator function optimized for maximal discriminative ability. In the proposed method \"M-GAIL\", the idea is that the discriminator is forced to also discriminate a third class of non-expert demonstrations, but policy optimization is done ignoring the non-expert demonstrations and classifying only the usual two classes with the discriminator.\n\nThe M-GAIL method is compared to GAIL on four control tasks with different amounts of simulated non-expert demonstrations available, and it outperforms GAIL if the simulated non-expert demonstrations are chosen to be relatively good ones (simulated from a policy having 70% of expert performance).\n\n\nEvaluation:\n\nThe method is described relatively well and the idea of incorporating nonexpert demonstrations seems sound.\n\nIt is not clear to me if the experiment is fair, since M-GAIL learns from more data than GAIL which learns from the expert demonstrations only. It is unclear to me why the experiments did not attempt to supply the nonexpert demonstrations to GAIL too - one could e.g. have naively pooled the nonexpert demonstration into one of GAIL's binary classes, \"expert\" or \"policy\". This is especially concerning since bett\n\nThe method also requires the additional parameter lambda which affects performance in the experiments - it is not clear how to set it in practice, does e.g. cross-validation etc. need to be used? It would be useful to know more about sensitivity to lambda, experiments only consider two values.\n\n\nAdditional comments:\n\nIn the methodological derivation, it was unclear to me why only one parameter lambda is used to control class balance, why not two parameters controlling prevalence of the expert class, policy class, and nonexpert class?\n\nIn proposition 1 the fact that the bias vanishes when lambda=0 seems trivial because eq. 9 reduces to the first term on the right hand side.\n\nIn eq. 5 it's not quite right to call the right-hand side a loglikelihood. Loglikelihoods should be sums over observations of each class (thus emphasizing classes with more data) whereas here each term is an expectation - or do you assume the number of samples corresponding to each expectation term is equal?\n\nClarify the notation d_phi when you introduce it near eq. 3.\n", "rating": "5: Marginally below acceptance threshold", "confidence": "3: The reviewer is fairly confident that the evaluation is correct"}, "signatures": ["ICLR.cc/2019/Conference/Paper575/AnonReviewer1"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2019/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations", "abstract": "Imitation learning aims to learn an optimal policy from expert demonstrations and its recent combination with deep learning has shown impressive performance. However, collecting a large number of expert demonstrations for deep learning is time-consuming and requires much expert effort. In this paper, we propose a method to improve generative adversarial imitation learning by using additional information from non-expert demonstrations which are easier to obtain. The key idea of our method is to perform multiclass classification to learn discriminator functions where non-expert demonstrations are regarded as being drawn from an extra class. Experiments in continuous control tasks demonstrate that our method learns better policies than the generative adversarial imitation learning baseline when the number of expert demonstrations is small.", "keywords": ["Imitation learning", "Generative adversarial imitation learning"], "authorids": ["voot.tangkaratt@riken.jp", "sugi@k.u-tokyo.ac.jp"], "authors": ["Voot Tangkaratt", "Masashi Sugiyama"], "TL;DR": "We improve GAIL by learning discriminators using multiclass classification with non-expert regarded as an extra class.", "pdf": "/pdf/3bd7072ceff083939e4740be0cd7f1f2ef0dffdc.pdf", "paperhash": "tangkaratt|improving_generative_adversarial_imitation_learning_with_nonexpert_demonstrations", "_bibtex": "@misc{\ntangkaratt2019improving,\ntitle={Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations},\nauthor={Voot Tangkaratt and Masashi Sugiyama},\nyear={2019},\nurl={https://openreview.net/forum?id=BJl65sA9tm},\n}"}, "tags": [], "invitation": {"id": "ICLR.cc/2019/Conference/-/Paper575/Official_Review", "cdate": 1542234429840, "expdate": 1552335264000, "duedate": 1541116800000, "reply": {"forum": "BJl65sA9tm", "replyto": "BJl65sA9tm", "readers": {"description": "The users who will be allowed to read the reply content.", "values": ["everyone"]}, "nonreaders": {"values": []}, "signatures": {"description": "How your identity will be displayed with the above content.", "values-regex": "ICLR.cc/2019/Conference/Paper575/AnonReviewer[0-9]+"}, "writers": {"description": "Users that may modify this record.", "values": ["ICLR.cc/2019/Conference"]}, "content": {"title": {"order": 1, "value-regex": ".{0,500}", "description": "Brief summary of your review.", "required": true}, "review": {"order": 2, "value-regex": "[\\S\\s]{1,200000}", "description": "Please provide an evaluation of the quality, clarity, originality and significance of this work, including a list of its pros and cons (max 200000 characters).", "required": true}, "rating": {"order": 3, "value-dropdown": ["10: Top 5% of accepted papers, seminal paper", "9: Top 15% of accepted papers, strong accept", "8: Top 50% of accepted papers, clear accept", "7: Good paper, accept", "6: Marginally above acceptance threshold", "5: Marginally below acceptance threshold", "4: Ok but not good enough - rejection", "3: Clear rejection", "2: Strong rejection", "1: Trivial or wrong"], "required": true}, "confidence": {"order": 4, "value-radio": ["5: The reviewer is absolutely certain that the evaluation is correct and very familiar with the relevant literature", "4: The reviewer is confident but not absolutely certain that the evaluation is correct", "3: The reviewer is fairly confident that the evaluation is correct", "2: The reviewer is willing to defend the evaluation, but it is quite likely that the reviewer did not understand central parts of the paper", "1: The reviewer's evaluation is an educated guess"], "required": true}}}, "multiReply": false, "tcdate": 1552335755677, "tmdate": 1552335755677, "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2019/Conference"], "invitees": ["ICLR.cc/2019/Conference/Paper575/Reviewers"], "noninvitees": [], "signatures": ["ICLR.cc/2019/Conference"]}}}, {"id": "BygZOLGGaQ", "original": null, "number": 3, "cdate": 1541707369227, "ddate": null, "tcdate": 1541707369227, "tmdate": 1541707369227, "tddate": null, "forum": "BJl65sA9tm", "replyto": "BJl65sA9tm", "invitation": "ICLR.cc/2019/Conference/-/Paper575/Official_Review", "content": {"title": "Formulation seems unnecessary compared to existing imitation learning frameworks", "review": "This paper proposes M-GAIL, which performs imitation learning from expert as well as sub-optimal demonstrations. This work builds off of GAIL (Ho et. al 2016) but modifies the discriminator with an additional class corresponding to sub-optimal demonstrations. The authors show empirically that including these sub-optimal demonstrations into the training process leads to faster and improved learning.\n\nWhile allowing the use of sub-optimal demonstrations is important and could have useful benefits in practice, I find the new algorithmic formulation unnecessary when compared to previous works. One of the theoretical benefits of MaxCausalEnt IRL (and by extension GAIL) is that because the model is probabilistic, not all demonstrations need to be reward-maximizing. The definition of optimality is relaxed from meaning exact reward maximization to coming from some optimal distribution over trajectories.\n\nCorrect me if I am wrong, but in the case of this work, the proposed algorithm seems equivalent to adding the \"sub-optimal\" demonstrations to the expert demonstrations, but down-weighting each sub-optimal demonstration be a factor of \\lambda. Thus, I don't believe we need to introduce an entirely new algorithm, with the concept of a 3rd class, to solve this problem. The existing MaxEnt frameworks seem to handle the notion of sub-optimality proposed in this paper just as well, interpreting the \"sub-optimal\" demonstrations as low-probability expert demonstrations. This feels cleaner and more intuitive than the current proposed explanation as maximizing a mixture of two reward functions (in the IRL view) or minimizing occupancy measure divergence over 3 distributions (in the IL view). If this equivalence is true, I would encourage the authors to include this discussion in the main paper, and if not, discuss the differences and possibly compare against this simple strategy as a baseline.\n\nI find the empirical results quite interesting, even though the gains seem small. Including sub-optimal demonstrations to learn from could be a nice trick to improve the learning of GAIL-like algorithms, which is nice to know. I am curious if the authors tried annealing the \\lambda term from 1.0 to 0.0, as lambda=1.0 is likely easier to learn from, but lambda=0.0 would have better asymptotic performance.", "rating": "5: Marginally below acceptance threshold", "confidence": "4: The reviewer is confident but not absolutely certain that the evaluation is correct"}, "signatures": ["ICLR.cc/2019/Conference/Paper575/AnonReviewer4"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2019/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations", "abstract": "Imitation learning aims to learn an optimal policy from expert demonstrations and its recent combination with deep learning has shown impressive performance. However, collecting a large number of expert demonstrations for deep learning is time-consuming and requires much expert effort. In this paper, we propose a method to improve generative adversarial imitation learning by using additional information from non-expert demonstrations which are easier to obtain. The key idea of our method is to perform multiclass classification to learn discriminator functions where non-expert demonstrations are regarded as being drawn from an extra class. Experiments in continuous control tasks demonstrate that our method learns better policies than the generative adversarial imitation learning baseline when the number of expert demonstrations is small.", "keywords": ["Imitation learning", "Generative adversarial imitation learning"], "authorids": ["voot.tangkaratt@riken.jp", "sugi@k.u-tokyo.ac.jp"], "authors": ["Voot Tangkaratt", "Masashi Sugiyama"], "TL;DR": "We improve GAIL by learning discriminators using multiclass classification with non-expert regarded as an extra class.", "pdf": "/pdf/3bd7072ceff083939e4740be0cd7f1f2ef0dffdc.pdf", "paperhash": "tangkaratt|improving_generative_adversarial_imitation_learning_with_nonexpert_demonstrations", "_bibtex": "@misc{\ntangkaratt2019improving,\ntitle={Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations},\nauthor={Voot Tangkaratt and Masashi Sugiyama},\nyear={2019},\nurl={https://openreview.net/forum?id=BJl65sA9tm},\n}"}, "tags": [], "invitation": {"id": "ICLR.cc/2019/Conference/-/Paper575/Official_Review", "cdate": 1542234429840, "expdate": 1552335264000, "duedate": 1541116800000, "reply": {"forum": "BJl65sA9tm", "replyto": "BJl65sA9tm", "readers": {"description": "The users who will be allowed to read the reply content.", "values": ["everyone"]}, "nonreaders": {"values": []}, "signatures": {"description": "How your identity will be displayed with the above content.", "values-regex": "ICLR.cc/2019/Conference/Paper575/AnonReviewer[0-9]+"}, "writers": {"description": "Users that may modify this record.", "values": ["ICLR.cc/2019/Conference"]}, "content": {"title": {"order": 1, "value-regex": ".{0,500}", "description": "Brief summary of your review.", "required": true}, "review": {"order": 2, "value-regex": "[\\S\\s]{1,200000}", "description": "Please provide an evaluation of the quality, clarity, originality and significance of this work, including a list of its pros and cons (max 200000 characters).", "required": true}, "rating": {"order": 3, "value-dropdown": ["10: Top 5% of accepted papers, seminal paper", "9: Top 15% of accepted papers, strong accept", "8: Top 50% of accepted papers, clear accept", "7: Good paper, accept", "6: Marginally above acceptance threshold", "5: Marginally below acceptance threshold", "4: Ok but not good enough - rejection", "3: Clear rejection", "2: Strong rejection", "1: Trivial or wrong"], "required": true}, "confidence": {"order": 4, "value-radio": ["5: The reviewer is absolutely certain that the evaluation is correct and very familiar with the relevant literature", "4: The reviewer is confident but not absolutely certain that the evaluation is correct", "3: The reviewer is fairly confident that the evaluation is correct", "2: The reviewer is willing to defend the evaluation, but it is quite likely that the reviewer did not understand central parts of the paper", "1: The reviewer's evaluation is an educated guess"], "required": true}}}, "multiReply": false, "tcdate": 1552335755677, "tmdate": 1552335755677, "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2019/Conference"], "invitees": ["ICLR.cc/2019/Conference/Paper575/Reviewers"], "noninvitees": [], "signatures": ["ICLR.cc/2019/Conference"]}}}, {"id": "S1g02-Kc3X", "original": null, "number": 2, "cdate": 1541210549976, "ddate": null, "tcdate": 1541210549976, "tmdate": 1541533876191, "tddate": null, "forum": "BJl65sA9tm", "replyto": "BJl65sA9tm", "invitation": "ICLR.cc/2019/Conference/-/Paper575/Official_Review", "content": {"title": "Intersting idea", "review": "Summary:\nThis paper is about adversarial imitation learning and how data from non experts can be used to improve representation learning of the discriminator function. They also change the training objective because minmax does not lead to an optimal policy in the proposed setting. The data from non experts is used a separate class (so the discriminator learns to discriminate between expert, agent and non-expert policy). \n\nClarity: well written, with an intro to both relative fields - reinforcement learning and imitation learning. \n\nComments:\nOverall, quite a neat idea - the information from non expert policy can help with representation learning, and the authors show that it is indeed the case via a number of experiments \nAt the same time, i wonder if the third class is required. It seems that gail in the experiments eventually reaches the same performance (figure 1) by looking at more agents trajectories. why can't non expert trajectories be considered as an initial set of agent trajectories? If multiclass is indeed required, it would be nice to see a comparison of what happens when non experts trajectories were just considered agents\nAnother thing i am surprised about is the leel of variance of GAIL in Figure 1. In table 1 we see that standard errors between the new method and gail are comparable, where does such a huge diff in var come from in Figure 1?\nAlso the sensitivity of the algorithm to lambda - how would one go setting it? In the experiments it seems that authors just try two different values (0.1 and 0.5) but i assume this really should be a hyperparameter search for this. Is lambda dependent on the number of expert and non expert demonstrations that are available?\n\n\n\n", "rating": "7: Good paper, accept", "confidence": "3: The reviewer is fairly confident that the evaluation is correct"}, "signatures": ["ICLR.cc/2019/Conference/Paper575/AnonReviewer2"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2019/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations", "abstract": "Imitation learning aims to learn an optimal policy from expert demonstrations and its recent combination with deep learning has shown impressive performance. However, collecting a large number of expert demonstrations for deep learning is time-consuming and requires much expert effort. In this paper, we propose a method to improve generative adversarial imitation learning by using additional information from non-expert demonstrations which are easier to obtain. The key idea of our method is to perform multiclass classification to learn discriminator functions where non-expert demonstrations are regarded as being drawn from an extra class. Experiments in continuous control tasks demonstrate that our method learns better policies than the generative adversarial imitation learning baseline when the number of expert demonstrations is small.", "keywords": ["Imitation learning", "Generative adversarial imitation learning"], "authorids": ["voot.tangkaratt@riken.jp", "sugi@k.u-tokyo.ac.jp"], "authors": ["Voot Tangkaratt", "Masashi Sugiyama"], "TL;DR": "We improve GAIL by learning discriminators using multiclass classification with non-expert regarded as an extra class.", "pdf": "/pdf/3bd7072ceff083939e4740be0cd7f1f2ef0dffdc.pdf", "paperhash": "tangkaratt|improving_generative_adversarial_imitation_learning_with_nonexpert_demonstrations", "_bibtex": "@misc{\ntangkaratt2019improving,\ntitle={Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations},\nauthor={Voot Tangkaratt and Masashi Sugiyama},\nyear={2019},\nurl={https://openreview.net/forum?id=BJl65sA9tm},\n}"}, "tags": [], "invitation": {"id": "ICLR.cc/2019/Conference/-/Paper575/Official_Review", "cdate": 1542234429840, "expdate": 1552335264000, "duedate": 1541116800000, "reply": {"forum": "BJl65sA9tm", "replyto": "BJl65sA9tm", "readers": {"description": "The users who will be allowed to read the reply content.", "values": ["everyone"]}, "nonreaders": {"values": []}, "signatures": {"description": "How your identity will be displayed with the above content.", "values-regex": "ICLR.cc/2019/Conference/Paper575/AnonReviewer[0-9]+"}, "writers": {"description": "Users that may modify this record.", "values": ["ICLR.cc/2019/Conference"]}, "content": {"title": {"order": 1, "value-regex": ".{0,500}", "description": "Brief summary of your review.", "required": true}, "review": {"order": 2, "value-regex": "[\\S\\s]{1,200000}", "description": "Please provide an evaluation of the quality, clarity, originality and significance of this work, including a list of its pros and cons (max 200000 characters).", "required": true}, "rating": {"order": 3, "value-dropdown": ["10: Top 5% of accepted papers, seminal paper", "9: Top 15% of accepted papers, strong accept", "8: Top 50% of accepted papers, clear accept", "7: Good paper, accept", "6: Marginally above acceptance threshold", "5: Marginally below acceptance threshold", "4: Ok but not good enough - rejection", "3: Clear rejection", "2: Strong rejection", "1: Trivial or wrong"], "required": true}, "confidence": {"order": 4, "value-radio": ["5: The reviewer is absolutely certain that the evaluation is correct and very familiar with the relevant literature", "4: The reviewer is confident but not absolutely certain that the evaluation is correct", "3: The reviewer is fairly confident that the evaluation is correct", "2: The reviewer is willing to defend the evaluation, but it is quite likely that the reviewer did not understand central parts of the paper", "1: The reviewer's evaluation is an educated guess"], "required": true}}}, "multiReply": false, "tcdate": 1552335755677, "tmdate": 1552335755677, "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2019/Conference"], "invitees": ["ICLR.cc/2019/Conference/Paper575/Reviewers"], "noninvitees": [], "signatures": ["ICLR.cc/2019/Conference"]}}}, {"id": "rklN7J19hQ", "original": null, "number": 1, "cdate": 1541168923652, "ddate": null, "tcdate": 1541168923652, "tmdate": 1541533875983, "tddate": null, "forum": "BJl65sA9tm", "replyto": "BJl65sA9tm", "invitation": "ICLR.cc/2019/Conference/-/Paper575/Official_Review", "content": {"title": "too little contribution", "review": "The paper proposes a modification of GAIL (Ho & Ermon, 2016) to make use of non-expert data. The non-expert data is used by training a classifier to classify between roll-outs of the current policy, expert demonstrations and non-expert demonstrations. Similar to GAIL, the policy is iteratively updated using TRPO with a cost that is given by the log probability of predicting the policy. The use of non-expert data acts as regularization in order to learn better features similar to universum prescription (Zhang & LeCun, 2017). \n\nThe paper is well-written and very clear. The general problem setting is interesting, but I think it is of rather little significance, because I do not see many clear applications. The evaluation focuses on simulated robots, however gathering non-expert data on real robots would be very expensive, so the approach would not make a lot of sense here (even if we replace TRPO a more sample efficient rl method). The paper mentions the game of Go, but learning a policy on such large state spaces is not feasible without major modification and significant computational effort. However, the paper also mentions autonomous driving, which might be a more convincing application, because we can have a lot of demonstrations that we do not want to label as expert trajectories. I think the paper would profit a lot from having an experiment where the importance of making use of non-expert data becomes evident.\n\nThe approach seems sound, although I think that we can not expect much benefit from using the unlabelled data in the proposed way. By not making any assumptions on the non-expert data, they do not carry any information about the objective; the information that they carry about the system dynamics is not exploited for the RL update. Instead, the use of non-expert data is restricted to learning better features for discriminating between the agent and the expert. However, non-expert data is typically not cheaper than policy roll-outs and better features could also be learned by using more samples from the policy. The experiments also show only slight benefits, especially when comparing the final performance (instead of total returns) and accounting for the additional system interactions needed for generating the non-expert data. To make the comparison fairer, we could consider using a few more system interactions (variable K in the paper) per iteration for standard GAIL, so that the total number of function evaluations would match those of M-GAIL after a certain number of iterations. Especially if K is appropriately tuned, it is not clear whether we could still show an advantage of M-GAIL. It would also be interesting to show, whether we can benefit from using the policy roll-outs of previous iterations as non-expert data for the current iteration (in the traditional IL setting where no non-expert data is available a priori).\n\nThe main weakness of the paper is, that the novelty seems marginal. Instead of doing binary classification with cross-entropy loss, we're doing three-class classification with cross-entropy loss and use it for binary classification (by throwing away the auxiliary logit for predicting the non-expert class). Did I miss any other difference to GAIL? We can argue whether the policy objective is different (to me, H_\\phi of M-GAIL corresponds to the discriminator of GAIL and the objective is exactly the same), however, even if we call it a minor modification, we would have very little novelty in the approach. As the paper does also not compensate for this with very good results or thorough theoretical analysis, I think that the contribution is too minor.\n\nI do not see the point of section 4.4. and the related appendix A2. For all I understand, it proves that when using lambda=0 (standard GAIL, right?), the proof of Fu et al. (2018) for GAIL is valid (i.e. we learn a completely useless reward function that does not carry any additional information compared to the policy), and when using lambda!=0 we learn something different. I don't see the the purpose of this statement and I don't think that it needs to be proven. The paper argues, that for small lambda we can treat the discriminator logits as approximations of these (completely useless) reward functions--without providing any bound. As I do not see why this would be useful, I think the section should be removed. \n\nMinor:\nTypo: \"[...]due to its dependent[sic] on the linearity of reward functions and good feature engineering\" \n", "rating": "4: Ok but not good enough - rejection", "confidence": "5: The reviewer is absolutely certain that the evaluation is correct and very familiar with the relevant literature"}, "signatures": ["ICLR.cc/2019/Conference/Paper575/AnonReviewer3"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2019/Conference"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations", "abstract": "Imitation learning aims to learn an optimal policy from expert demonstrations and its recent combination with deep learning has shown impressive performance. However, collecting a large number of expert demonstrations for deep learning is time-consuming and requires much expert effort. In this paper, we propose a method to improve generative adversarial imitation learning by using additional information from non-expert demonstrations which are easier to obtain. The key idea of our method is to perform multiclass classification to learn discriminator functions where non-expert demonstrations are regarded as being drawn from an extra class. Experiments in continuous control tasks demonstrate that our method learns better policies than the generative adversarial imitation learning baseline when the number of expert demonstrations is small.", "keywords": ["Imitation learning", "Generative adversarial imitation learning"], "authorids": ["voot.tangkaratt@riken.jp", "sugi@k.u-tokyo.ac.jp"], "authors": ["Voot Tangkaratt", "Masashi Sugiyama"], "TL;DR": "We improve GAIL by learning discriminators using multiclass classification with non-expert regarded as an extra class.", "pdf": "/pdf/3bd7072ceff083939e4740be0cd7f1f2ef0dffdc.pdf", "paperhash": "tangkaratt|improving_generative_adversarial_imitation_learning_with_nonexpert_demonstrations", "_bibtex": "@misc{\ntangkaratt2019improving,\ntitle={Improving Generative Adversarial Imitation Learning with Non-expert Demonstrations},\nauthor={Voot Tangkaratt and Masashi Sugiyama},\nyear={2019},\nurl={https://openreview.net/forum?id=BJl65sA9tm},\n}"}, "tags": [], "invitation": {"id": "ICLR.cc/2019/Conference/-/Paper575/Official_Review", "cdate": 1542234429840, "expdate": 1552335264000, "duedate": 1541116800000, "reply": {"forum": "BJl65sA9tm", "replyto": "BJl65sA9tm", "readers": {"description": "The users who will be allowed to read the reply content.", "values": ["everyone"]}, "nonreaders": {"values": []}, "signatures": {"description": "How your identity will be displayed with the above content.", "values-regex": "ICLR.cc/2019/Conference/Paper575/AnonReviewer[0-9]+"}, "writers": {"description": "Users that may modify this record.", "values": ["ICLR.cc/2019/Conference"]}, "content": {"title": {"order": 1, "value-regex": ".{0,500}", "description": "Brief summary of your review.", "required": true}, "review": {"order": 2, "value-regex": "[\\S\\s]{1,200000}", "description": "Please provide an evaluation of the quality, clarity, originality and significance of this work, including a list of its pros and cons (max 200000 characters).", "required": true}, "rating": {"order": 3, "value-dropdown": ["10: Top 5% of accepted papers, seminal paper", "9: Top 15% of accepted papers, strong accept", "8: Top 50% of accepted papers, clear accept", "7: Good paper, accept", "6: Marginally above acceptance threshold", "5: Marginally below acceptance threshold", "4: Ok but not good enough - rejection", "3: Clear rejection", "2: Strong rejection", "1: Trivial or wrong"], "required": true}, "confidence": {"order": 4, "value-radio": ["5: The reviewer is absolutely certain that the evaluation is correct and very familiar with the relevant literature", "4: The reviewer is confident but not absolutely certain that the evaluation is correct", "3: The reviewer is fairly confident that the evaluation is correct", "2: The reviewer is willing to defend the evaluation, but it is quite likely that the reviewer did not understand central parts of the paper", "1: The reviewer's evaluation is an educated guess"], "required": true}}}, "multiReply": false, "tcdate": 1552335755677, "tmdate": 1552335755677, "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2019/Conference"], "invitees": ["ICLR.cc/2019/Conference/Paper575/Reviewers"], "noninvitees": [], "signatures": ["ICLR.cc/2019/Conference"]}}}], "count": 15}
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{"title":"Shutter.Island.2010.480p.BDRip.LiNE.XviD-ViSiON","uid":5466716,"size":2566454540,"categoryP":"video","categoryS":"movies","magnet":"?xt=urn:btih:621f87983c1442378ca0762926038b2c21416a8a&amp;dn=Shutter.Island.2010.480p.BDRip.LiNE.XviD-ViSiON&amp;tr=udp%3A%2F%2Ftracker.openbittorrent.com%3A80&amp;tr=udp%3A%2F%2Fopen.demonii.com%3A1337&amp;tr=udp%3A%2F%2Ftracker.coppersurfer.tk%3A6969&amp;tr=udp%3A%2F%2Fexodus.desync.com%3A6969","seeders":0,"leechers":0,"uploader":"raymondhome","files":-1,"time":1269653620,"description":"Love for All and Sharing is the first step to solving all the problems of humanity.\n\nWebsites I want to share.\n\n &lt;a href=&quot;\nhttp://www.shareintl.org/&quot; rel=&quot;nofollow&quot; target=&quot;_NEW&quot;&gt;\nhttp://www.shareintl.org/&lt;/a&gt;\n\n &lt;a href=&quot;\nhttp://www.lightmiddleway.com&quot; rel=&quot;nofollow&quot; target=&quot;_NEW&quot;&gt;\nhttp://www.lightmiddleway.com&lt;/a&gt;\n\n\nThank you very much\n\nNo credit for me...credit to EVERYONE for sharing\n &lt;a href=&quot;\nhttp://thepiratebay.se/user/raymondhome/&quot; rel=&quot;nofollow&quot; target=&quot;_NEW&quot;&gt;\nhttp://thepiratebay.se/user/raymondhome/&lt;/a&gt;\n\nPLOT\nDrama is set in 1954, U.S. Marshal Teddy Daniels is investigating the disappearance of a murderess who escaped from a hospital for the criminally insane and is presumed to be hiding on the remote Shutter Island.\n\nIMDb RATING: 8.1/10 (47,079 votes - Top 250: #217)\n\nRuntime......: 138 Min\nSource.......: BDISC Russian [40GB]\nResolution...: 720x304\nSA...........: BVOP: YES QPEL: NO GMC: NO\nFramerate....: 24.000\nVideo........: 2254 Kbps\nAudio........: 192 Kbps iMGAINE-PRiSM THNX!\nLanguage.....: English\nEncoder......: oZi\n\nViSiON NOTES\nWe tagged this as BDRip, because source is from an Russian Bluray. Audio is from iMAGINE and synced by PRiSM, both THNX. Its still a LiNE audio, dont think its retail.\n\ncredit ViSiON &amp; oZi &amp; to all the people who made it possible for me to share this with everyone\n\nUPLOAD DEDICATED TO redchaos2354, Motley Crue, jdpennington, BADASS, W1ck3d1nt3ntz, ceo54, DaRkReAlM, ghostman, karakurachow, megaplay, Emery1337x, SaM, geordieboy1979, timamirrockdude, Noir, Shedevil, bone111, JorgeMontana, BlueLady, xxxUniversalAbsurdityxxx, mc68, TheFalcon007, pardeep333, X &amp; many, many more &amp; to all the awesome people who are sharing (ALL THE UPLOADERS, THE RIPPERS, THE SCENE GROUPS, ETC, THE WHOLE P2P COMMUNITY)***wish i could list everyone***Thank you very much everyone &amp; i mean EVERYONE!!!\n\n*****help what we can with haiti or any other in need...the world is ONE big family*****","torrent":{"xt":"urn:btih:621f87983c1442378ca0762926038b2c21416a8a","amp;dn":"Shutter.Island.2010.480p.BDRip.LiNE.XviD-ViSiON","amp;tr":["udp%3A%2F%2Ftracker.openbittorrent.com%3A80","udp%3A%2F%2Fopen.demonii.com%3A1337","udp%3A%2F%2Ftracker.coppersurfer.tk%3A6969","udp%3A%2F%2Fexodus.desync.com%3A6969"],"infoHash":"621f87983c1442378ca0762926038b2c21416a8a","infoHashBuffer":{"type":"Buffer","data":[98,31,135,152,60,20,66,55,140,160,118,41,38,3,139,44,33,65,106,138]},"announce":[],"urlList":[]}}
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stader har eit namn, men kvifor plassen har fått akkurat det namnet og kva det betyr er ikkje alltid så godt å vite.</p>","elements":{}},"body":{"text":"<p>I stadnamnserien vår har vi blant anna vore innom Kukkelurevika, ein plass der det fanst mange sniglehus. Vi har vore høgt til fjells på Håsteinen i Flora kommune. Hå betyr høg og er det høgste fjellet i området. Dermed vart namnet Håsteinen.</p>\n<ul> \n <li>Les også: \n <element localref=\"2220935c\"/></li> \n</ul>\n<p>Det litt artige namnet Gygrarøvi i Sogndal har og fått si forklaring. Segna fortel om ei trollkjerring som sette seg ned og laga merke i fjellet.</p>\n<p>\n <element localref=\"82d3c67d\"/></p>\n<p>\n <element localref=\"f710857a\"/></p>\n<p>\n <element localref=\"1c54ad9f\"/></p>\n<p>\n <element localref=\"5254e9f9\"/></p>\n<p>\n <element localref=\"960f6176\"/></p>\n<p>\n <element localref=\"8fc32304\"/></p>\n<p>\n <element localref=\"d8030ed3\"/></p>\n<p>\n <element localref=\"d58c38fc\"/></p>\n<p>\n <element localref=\"39e2439f\"/></p>\n<p>\n <element localref=\"39b7fd1c\"/></p>\n<p>\n <element localref=\"530e57a1\"/></p>\n<p>\n <element localref=\"ae80579f\"/></p>\n<p>\n <element localref=\"51dd823b\"/></p>\n<p>\n <element localref=\"a6162f60\"/></p>\n<p>\n <element localref=\"51dc1a3f\"/></p>\n<h2>Ivar Aasen si ordbok</h2>\n<p>I løpet av hausten skal du få vite kva meir om stadnamn som Bjørlo, Bembesvoda, Hafslo og mange fleire. Kristian Solvang har hovudfag i temaet og forskar på stadnamn. Han skal gje deg forklaring på små og store namn rundt om i heile Sogn og Fjordane, eit arbeid som krev både lokalkunnskap om gardsdeling og kystkultur.</p>\n<p>\n <element localref=\"2079d23e\"/></p>\n<p><strong>– Eg får stadig spørsmål frå folk som lurer på dette med namn. Det er ikkje alltid eg kan svare på ståande fot, og nokre stadnamn er det og vanskege å forklare, seier Solvang. Skal ein vere ein god tolkar av stadnamn, må ein ha mykje lokal kunnskap, blant anna om gardsdeling og kystkultur, fortel Solvang.</strong><br/> <br/> – For oss som undersøkjer stadnamn og gamle ord, vil eg kalle Ivar Aasen si ordbok for Bibelen.</p>\n<p>Serien, som er laga av Gro Ravnestad, skal du få i morgonsendinga kvar måndag og onsdag og vi legg og ut lydfilene og forklaringane på nettet. Vi tek gjerne imot spørsmål og tips. Du kan skrive dei inn i skjemaet under denne teksten.</p>\n<p>\n <element localref=\"23c7547a\"/></p>","elements":{"51dc1a3f":{"id":"1.13133501","targetType":"Audio","media":{"id":"1.13133501","type":"Audio","published":"2016-09-14T03:51:50Z","title":"Stadnamn-Tystigen.","remoteId":"280547"},"published":"2016-09-14T03:51:50Z","type":"Plug"},"d58c38fc":{"id":"1.13182456","targetType":"Audio","media":{"id":"1.13182456","type":"Audio","published":"2016-10-17T05:35:43Z","title":"Stadnamn - Ravnestad","remoteId":"284937"},"published":"2016-10-17T05:35:43Z","type":"Plug"},"2220935c":{"id":"1.12841664","targetType":"Article","title":"Kva betyr stadnamna? Vi treng tips","lead":"Rundt omkring på alle stadar i fylket finn vi namn på fjell, bakkar, tettstadar, øyar og skjær. Stadnamna fortel gjerne ei spennande historie og er ein viktig del av kulturarven vår.","image":{"crops":{"1521:856":{"80":"https://gfx-stage.nrk.no/CUGeJ1JSovWysZppIkMGAg3saqpv8mD-9VyYRpr5VFWA","160":"https://gfx-stage.nrk.no/CUGeJ1JSovWysZppIkMGAg345blbBXJoNVyYRpr5VFWA","350":"https://gfx-stage.nrk.no/CUGeJ1JSovWysZppIkMGAgEHdspd8x7txVyYRpr5VFWA","450":"https://gfx-stage.nrk.no/CUGeJ1JSovWysZppIkMGAgWq7ppw1088NVyYRpr5VFWA","650":"https://gfx-stage.nrk.no/CUGeJ1JSovWysZppIkMGAgBE06DqvkMcRVyYRpr5VFWA","1000":"https://gfx-stage.nrk.no/CUGeJ1JSovWysZppIkMGAgys-B1kXOHklVyYRpr5VFWA","1200":"https://gfx-stage.nrk.no/CUGeJ1JSovWysZppIkMGAgnCiwH59jvNdVyYRpr5VFWA","1600":"https://gfx-stage.nrk.no/CUGeJ1JSovWysZppIkMGAgTPdHgTJPnZFVyYRpr5VFWA","2000":"https://gfx-stage.nrk.no/CUGeJ1JSovWysZppIkMGAgTzneRp4_IXNVyYRpr5VFWA"}},"type":"ImageUrl"},"media":{"id":"1.12842010","type":"Video","published":"2016-03-08T11:49:09Z","title":"Lurer du på eit stadnamn?","description":"Rundt omkring på alle stadar i fylket finn vi namn på fjell, bakkar, tettstadar, øyar og skjær. 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{"ModuleCode":"CM4251","ModuleTitle":"Characterization Techniques in Materials Chemistry","Department":"Chemistry","ModuleDescription":"Preparation and characterization of materials form crucial and vital aspects of materials research. Highly developed instruments are now available to apply an interdisciplinary study to understand the structure-property relationship. This module provides undergraduates an introduction to modern materials characterization techniques which comprise surface analysis techniques, X-ray diffraction, microscopy, thermal analyses, mechanical tastings and spectroscopies.","ModuleCredit":"4","Workload":"4-1-0-1-4","Prerequisite":"CM3252 and CM3253","Types":["Module"],"History":[{"Semester":1,"ExamDate":"2018-11-27T09:00+0800","LecturePeriods":["Tuesday Afternoon","Thursday Afternoon"],"TutorialPeriods":["Wednesday Afternoon"]}]}
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{ "author": "1BIp2mpC", "id": "4IekiYfM", "title": "БАТЬКІВСЬКИЙ НАКАЗ", "link": "metrs_poem.php?poem=13486", "html": "\n<h4></h4>\n\n<a href=\"/metrs.php?id=65&amp;type=tvorch\" class=\"redhr1\">Творчість</a> |\n<a href=\"/metrs.php?id=65&amp;type=biogr\" class=\"redhr1\">Біографія</a> |\n<a href=\"/metrs.php?id=65&amp;type=critiques\" class=\"redhr1\">Критика</a>\n\n<h4>БАТЬКІВСЬКИЙ НАКАЗ</h4>\n<!--<div style=\"float:right;margin-left: 10px\">\n\t<script async src=\"//pagead2.googlesyndication.com/pagead/js/adsbygoogle.js\"></script>\n\n\t<ins class=\"adsbygoogle\"\n\t\t style=\"display:inline-block;width:250px;height:400px\"\n\t\t data-ad-client=\"ca-pub-5357335372099528\"\n\t\t data-ad-slot=\"7581761695\"></ins>\n\t<script>\n\t(adsbygoogle = window.adsbygoogle || []).push({});\n\t</script>\n</div>-->\n\nМій &nbsp;сину, &nbsp;бачу &nbsp;вже &nbsp;межу.<br>\nВона &nbsp;вимоглива &nbsp;і &nbsp;грізна.<br>\nСьогодні &nbsp;слова &nbsp;не &nbsp;скажу,<br>\nа &nbsp;завтра &nbsp;буде &nbsp;пізно.<br>\nЖиттєві &nbsp;істини &nbsp;прості,<br>\nненаче &nbsp;батьківські &nbsp;поради.<br>\nНе &nbsp;все &nbsp;можливо &nbsp;у &nbsp;житті<br>\nкупити &nbsp;чи &nbsp;продати.<br>\nРосте &nbsp;Вітчизна &nbsp;з &nbsp;порошин<br>\nі &nbsp;не &nbsp;прощає &nbsp;дешевизни.<br>\nНайбільше, &nbsp;сину, &nbsp;дорожи<br>\nлюбов'ю &nbsp;до &nbsp;Вітчизни.<br>\nЛюбов &nbsp;земна &nbsp;- &nbsp;не &nbsp;дивина,<br>\nта &nbsp;є &nbsp;призначення &nbsp;найвище:<br>\nлюби &nbsp;Вітчизну, &nbsp;щоб &nbsp;вона<br>\nне &nbsp;стала &nbsp;попелищем.<br>\nЛюбов &nbsp;на &nbsp;стоптаній &nbsp;золі<br>\nживими &nbsp;паростками &nbsp;бризне.<br>\nУсе &nbsp;найкраще &nbsp;на &nbsp;землі &nbsp;-<br>\nз &nbsp;любові &nbsp;до &nbsp;Вітчизни.<br>\nКоли &nbsp;на &nbsp;смертнім &nbsp;віражі<br>\nпітьма &nbsp;навік &nbsp;мене &nbsp;поглине, &nbsp;-<br>\nза &nbsp; &nbsp;мене, &nbsp;сину, &nbsp;збережи<br>\nлюбов &nbsp;неопалиму.<br>\nЯ &nbsp;всі &nbsp;негоди &nbsp;поборов,<br>\nщоб &nbsp;не &nbsp;взяла &nbsp;тебе &nbsp;трутизна.<br>\nМій &nbsp;сину, &nbsp;ти &nbsp;- &nbsp;моя &nbsp;любов<br>\nдо &nbsp;рідної &nbsp;Вітчизни.\n\n\n<br><br>\n" }
{ "name": "my-awesome-package" }
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{ "id": 12538, "source": "wen", "verse_id": 17887, "verse_count": 1, "reference": "11:2", "title": "", "html": "Wisdom - It is not needful, exactly to distinguish these two gifts; it is sufficient that they are necessary qualifications for a governor, and a teacher, and it is evident they signify perfect knowledge of all things necessary for his own and peoples good, and a sound judgment, to distinguish between things that differ. Counsel - Of prudence, to give good counsel; and of might and courage, to execute it. Knowledge - Of the perfect knowledge of the whole will and counsel of God, as also of all secret things, yea of the hearts of men. Fear - A fear of reverence, a care to please him, and lothness to offend him.", "audit": null }
{"artist": "Yung Lean", "songs": [{"album": "Stranger", "image": "https://images.genius.com/03a614a55c50781dfd2e7fd66efd0753.640x640x1.jpg", "year": "2017-10-20", "lyrics": "[Intro]\nGivench-\nAh, det skulle komma in d\u00e4r?\nSTRANGER\nAh, det kommer inte \u00e4n. Nu\nGivenchy\n\n[Verse 1]\nI got lots of swag and I be feelin' hurt\nWalk up in the bank like John Dillinger\nRainbows, I'm willin' to splurge\nAfter you've gone I'm still on the Earth\nNo, no, no you can't get my bank roll\nSlow, slow, slow this cup got me slow\nLow, low, low shawty bring it to the floor (get low)\nOh, oh, oh SBE in this bitch got more (Sad Boys)\n\n[Hook]\nSki mask, shawty, girl, whatever you like (you like)\nMoncler jackets dirty cash plenty flights (flights)\nCocaine clean but my jeans really dirty\nI just copped some silver rings and they go about Thirty\nSki mask, shawty I pull up with the team (pull up, pull up)\nSki mask, shawty I still see you in my dreams (Lean!)\nDirty fanta shawty, bitch, I'll never leave (l'll never leave)\nDirty fanta shawty, bitch, I'll never leave (Scrr, scrr)\n\n[Verse 2]\nFlow, flow, flow on the floor, floor, floor\nPercs, percs, percs, got me out of control\nIced-out on the floor rubber bands can't even fold\nGirls all in my phone ho ho Santa Clause\nSki mask shawty, prayin' down to my knees\nLouis Sprite Gang shawty all over me\nCheck out my waist and check out my sleeves\nWhen I ride around I keep my stacks on my feet\nSki mask shawty keep the racks for the team\nTen toes down in my head I'm not clean\nReality for me I don't see it like you see\nBroken Piano, pockets stuffed with magic beans\nWalk up in the club, I got like fifty birds (Walk up, Walk up)\nNeed this gun on me, I'm still on the search\nI got straight hunneds straight drop\nLove of my life she gonna set me up\nPull up, pull up, pull up, pull up in the parkin' lot\nBitch, we sellin' wine and I'm breakin' rocks\nJust keep goin' I don\u2019t wanna stop\nPull up, pull up in the parkin' lot\nDough, dough, dough, I got dough, dough, dough\nMore like Bart Simpson in my zone, zone, zone\nClone, clone, clone, you a clone, clone, clone\nAll so low Imma hop on the road\n\n[Hook]\nSki mask shawty got whatever you like\nMoncler jackets dirty cash plenty flights\nCocaine clean but my jeans really dirty\nI just copped some silver rings and they go about Thirty\nSki mask, shawty I pull up with the team (pull up, pull up)\nSki mask, shawty I still see you in my dreams (out of control)\nDirty fanta, shawty, bitch, I'll leave\nDirty fanta, shawty, bitch, I'll never leave\n\n[Outro]\nSanta clause, Leandoer, Stranger\nShout out Yung Gud, this is Gud my man, you already know\nSixhundred beats, sixhundred days, sixhundred songs\nI can\u2019t sleep no more gotta make another hit\nWake up in the mornin' and I make another hit\nYou know how it going' 'cause life is a bitch", "title": "Skimask"}]}
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var programa = new Programa("Olá mundo!"); programa.vars.criar('nome', 'literal'); programa.vars.criar('idade', 'real');
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{"poster":"Hnk Kenshiro","date":"2017-11-16T18:37:37.836+0000","title":"¿Podría activarse la E de Karthus cada 0,25 segundos?","subforum":"Jugabilidad, balance y narrativa","up_votes":25,"down_votes":2,"body":"http://ddragon.leagueoflegends.com/cdn/6.24.1/img/spell/KarthusDefile.png **Profanación**\n\n\nHabilidades que hagan daño el tiempo, se han cambiado para que hagan daño más seguido pero manteniendo el daño prolongado, ejemplos de esto son {{champion:27}} en el [**parche 6.19**](https://las.leagueoflegends.com/es/news/game-updates/patch/notas-de-la-version-619#patch-singed) y {{champion:9}} en el [**parche 4.15**](https://las.leagueoflegends.com/es/news/game-updates/patch/notas-de-la-version-415#patch-fiddlesticks).\n\n¿Podría Karthus aplicar el mismo daño en repeticiones más rápidas, para que sea más confiable dañar con la E en trades no tan largos?","replies":[{"poster":"IGNORE ALL","date":"2017-11-17T00:27:48.745+0000","up_votes":3,"down_votes":0,"body":"Este cambio se hizo una vez pero se deshizo(pbe) porque dificultaba el farmeo en early","replies":[]},{"poster":"El Impostor","date":"2017-11-17T03:04:58.917+0000","up_votes":2,"down_votes":0,"body":"Si tienes 45% de CDR y activas y desactivas rápidamente la E, haces mas daño que teniéndola activa continuamente xD\n\n(Al menos hace unos meses funcionaba así)","replies":[]},{"poster":"Salvor","date":"2017-11-16T18:56:48.316+0000","up_votes":2,"down_votes":1,"body":"De acuerdo muy.\n\nhttps://uploads.disquscdn.com/images/b16e5c089424f0e505a11bc83afb422ebe33dd48ba850bdf1a110299dc8970d8.jpg","replies":[]},{"poster":"LGBT Valentina","date":"2017-11-16T23:14:17.424+0000","up_votes":1,"down_votes":0,"body":"En si es un nerf esto, por eso no se hizo \n\nCuando activas la E de karthus hace daño al momento, en early-mid se nota esto","replies":[{"poster":"Hnk Kenshiro","date":"2017-11-17T00:08:55.612+0000","up_votes":1,"down_votes":0,"body":"Oh, suelo activarla poco antes de tocar al enemigo, por eso me salto ese daño inicial y tengo ese delay sin hacerle daño.\n\nSi esto es para mal, se entiende que se mantenga.","replies":[]}]},{"poster":"Predit","date":"2017-11-16T22:07:21.035+0000","up_votes":1,"down_votes":0,"body":"¿Y {{champion:136}} que su W tiene 4 segundos de cd que se notan cuando es stuneado?","replies":[]},{"poster":"SAD Katarina","date":"2017-11-16T19:13:58.184+0000","up_votes":1,"down_votes":0,"body":"https://ugc.kn3.net/i/origin/http://i.kinja-img.com/gawker-media/image/upload/s--nB_d8_QW--/17h9nmwjfi4wxpng.png","replies":[]}]}
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